PERFORMANCE

Issue No. 26 - Data Analytics, 2023 MAGAZINE

Data-driven
strategies
for business
success

Expert insights from Madhur

Mayank Sharma, Senior Director
and Head of AI Development at
SAP Asia PTE LTD

Beyond the hype: How can businesses

adopt technologies that matter?

Sustainable strategy in focus: leveraging

data to reduce environmental footprint
1
INDEMNITY STATEMENT

© 2023 The KPI Institute Ltd.

All Rights Reserved.
ID Number: TKI0232251
ISBN: 9798395536631

Imprint: Independently published

An appropriate citation for this magazine is:

The KPI Institute, Performance Magazine, Printed Edition, no. 26, July 2023, Melbourne, Australia

Indemnity statement:

The KPI Institute has taken due care in preparing the analysis contained in this publication. However,
noting that some of the data used for the analysis have been provided by third parties, The KPI Institute
gives no warranty to the accuracy, reliability, fitness for purpose, or otherwise of the information. The KPI
Institute shall have no liability for errors, omissions, or inadequacies in the information contained herein
or for interpretations thereof. The opinions expressed herein are subject to change without notice

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Editor’s Note
Data analytics empowers decision-making, strategy execution,
and leadership in business, but it is just a piece of the puzzle.
Surveys held by Ernst & Young and NewVantage Partners
show an increasing interest among company executives to
invest in data analytics and relevant capabilities. However,
cultural factors like insufficient data literacy and resistance to
change can hamper a company’s ability to derive value from
such investments. Organizations should take an integrated
approach to embracing data analytics if they want to take
advantage of the opportunities it presents in terms of achieving
sustainable business performance.

In this edition of Performance Magazine, we explore how data

analytics transforms the ways companies operate, develop Editorial Board
business strategies, and enhance performance management.
Our cover story goes into more detail about these, with exclusive Aurel Brudan
insights from Madhur Mayank Sharma, senior director and CEO, The KPI Institute
head of AI development at SAP Asia PTE LTD. Data analytics
experts from different industries share their insights on the Cristina Mihăiloaie
impact of modern tools like artificial intelligence on their field Business Unit Manager - Research
and how their organizations create a data strategy while Division, The KPI Institute
cultivating a data-driven culture.
Len Cristobal
Data analytics requires more than just technical knowledge. In Editor in Chief
this issue, we show how businesses can go beyond the hype when
adopting new technologies and how to bridge the knowledge Paolo Orduña
gap between data analysts and non-technical stakeholders. Senior Editor

The KPI Institute, which is celebrating its 19th year, has Kimberly Tilar
proven through its experience in research and performance Publisher and Editor Specialist
management that being equipped with the right knowledge
and tools makes a massive difference in adapting to trends. Daniela Vuta
Paired with a strategic mind frame, education can help Technical Editor and Head of
organizations integrate data analytics into their work culture, Publications
bringing about measurable and meaningful results.
Islam Salahuddin
Data Analyst and Guest Editor

Liana Paraschiv
Andreana Dumitrescu
Andra Rotar
Len Cristobal Roxana Barb
Editor in Chief, Fadi Al-Jafari
Performance Magazine Layla Woodard
Writers

Nouran Essam & Mohamed Fouad

Design & Layout Artist
CONTENTS OVERVIEW

NEWS
News 01
Business Trends - Artificial Intelligence - Data Analytics
TKI uncovers 2023 global trends impacting
strategy, performance management

Interviews 08
Data buddies: bridging the gap between data
analysts and non-technical team members

Cover Story 27
Strength in numbers: embracing dynamic data
strategies for business transformation

In-depth 30

Sustainable strategy in focus: leveraging data
to reduce environmental footprint

Ask Our Experts 47

How can organizations bridge the knowledge
gap between data analysts and non-technical
stakeholders and decision-makers?

Career Insights 51
Overlooking statistics in data analytics
courses: a dangerous mistake
1
 NEWS NEWS

TKI uncovers 2023 global trends

impacting strategy, performance
management

The KPI Institute successfully hosted a forum The webinar covered trends in the realms of Figure 1. Business Pulse: Five Trends Impacting Strategy and Performance Management
on global trends that will impact strategy and geopolitics, economics, society and culture,
performance management practices in 2023. technology, and sustainability. Through careful “As Peter Drucker said, 'The best way to predict performance management skills, you may want
Dubbed “2023 Business Pulse: 5 Trends Impacting analysis of these trends, the experts identified the the future is to create it,' and this seminar has to check out our courses. Arm yourselves with the
Strategy and Performance Management,” the most possible trajectories that will shape the future equipped our participants with the knowledge knowledge that you need to successfully ride the
webinar was hosted by the TKI Research Division’s of strategy and performance management (see and understanding to do just that,” said Cristina. business world’s ever-changing trends here.
business unit manager, Cristina Mihailoaie, and Figure 1). If you have a yearning for learning strategy and
data expert, Islam Salahuddin.

2 3
 NEWS NEWS

Customer interactions have also been revolutionized If you want to learn more about how to leverage
NEWS FEATURE
by AI. According to the aforementioned Forbes this revolutionary technology, maentae has teamed

How artificial intelligence is report, 64% of business owners acknowledge AI's up with The KPI Institute and AMSI to offer a
potential in improving customer relationships, course on how to integrate AI technology to boost
demonstrated by how AI-powered chatbots and productivity. This meticulously crafted program
reshaping the business landscape virtual assistants have become valuable assets
for personalized and efficient customer support.
comprises a comprehensive curriculum that
equips participants with the essential knowledge
Furthermore, AI-driven recommendation systems and proficiency to skillfully navigate the intricate
Layla Woodard
enhance customer experiences by offering tailored AI landscape and harness its transformative
product suggestions and personalized offers. capabilities for organizational triumph.

As AI continues to evolve and mature, its impact Contact Alexandru Muntean, head of customer
becomes more significant and indispensable. engagement: alex.muntean@kpiinstitute.com +40
Organizations must embrace AI to stay competitive 747 060 997. Embark on a transformative learning
and capitalize on its transformative potential. AI journey where the possibilities of AI become the
adoption is no longer an option but a necessity for driving force behind your future achievements.
businesses that seek to gain a competitive edge in
today's dynamic landscape.

About maentae

maentae is a next-generation provider of impactful learning journeys that empower individuals

across all levels of expertise to thrive in the ever-evolving landscape of the modern workforce.
At the heart of maentae's philosophy lies a fusion of science, art, and technology. By embracing
the synergy between rigorous academic research and practice-driven insights, maentae is shaping
curricula that break traditional boundaries.
As artificial intelligence (AI) transitions from creation and multilingual content generation,
novelty to necessity, its transformative impact on highlighting its broad appeal and potential impact.
everything— from the personal to the professional—
is becoming increasingly apparent. How exactly is AI's transformative power lies in its ability to
this technology reshaping the business landscape? automate mundane tasks, freeing up human
resources for more strategic endeavors. By
AI has moved from the realm of science fiction harnessing AI-driven automation, businesses can
into science fact, becoming an integral part of our enhance productivity, reduce costs, and allocate
daily lives in the process. From voice assistants on talent to value-adding activities. Additionally,
our smartphones to personalized recommendations AI empowers organizations to unlock actionable
on streaming platforms, AI has permeated various insights from vast datasets, enabling data-driven
aspects of our everyday experiences. decision-making for a competitive advantage.

However, AI isn’t just impacting our personal lives, Additionally, AI's analytical capabilities can help
it is also becoming an essential part of the modern businesses and professionals extract valuable
workplace. In the business landscape, AI offers a insights from vast datasets, uncovering realizations
range of opportunities for organizations to drive that support more informed decision-making.
efficiency, innovation, and customer engagement. Through exploring intricate patterns, trends, and
According to a report by Forbes Advisor, an correlations, AI-driven analytics can equip business
overwhelming 97% of business owners recognize the professionals with actionable insights to enhance
benefits of ChatGPT. A significant portion (44%) operations, deepen customer experiences, and
intends to leverage ChatGPT for website content pinpoint untapped market prospects.

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 NEWS NEWS

INDUSTRY NEWS

Gartner Data & Analytics Summit 2028 outlook: smart grid

data analytics market
2023 explores data-driven business
experiences continued
transformation growth

IMARC Group recently released its latest report, “Smart Grid Data Data mining services
Analytics Market: Global Industry Trends, Share, Size, Growth,
demand set to increase
Opportunity and Forecast 2023-2028.” This comprehensive analysis
offers insights into the smart grid data analytics market share, in 2023
competitor and regional analysis, and contemporary advancements The mining software and
in the industry. services industry is expected
to exhibit a compound
According to the report, the global smart grid data analytics market annual growth rate of 11.9%,
size reached US$ 2.2 Billion in 2022, and IMARC Group expects the resulting in growth from
market to grow at a compound annual growth rate of 10.87% from 519.3 USD million in 2017
2023 to 2028. to 1,039.1 USD million in
2023, according to the Data
In 2023, artificial intelligence (AI) algorithms will likely become more Mining Tools Market report
prevalent in managing smart grids based on Hive Power’s “Top 5 by MarketsandMarkets™.
Smart Grids Trends to Expect in 2023.” The report suggests that with The growth is attributed
the ability to forecast demand, detect potential problems in advance, to the considerable surge
and optimize grid operations, these algorithms will enhance energy in data volume and
flow management, grid efficiency, and reliability. growing recognition among
enterprises of the advantages
Sources: of utilizing available data
Digital Journal assets.
Hive Power
MarketsandMarkets™ shared
Data and analytics leaders from around the world survey results emphasizing the importance of that data mining service
gathered in Orlando, Florida, for the Gartner Data presence, persistence, and performance for the providers offer substantial
& Analytics Summit held in the first quarter of thesuccess of Chief Data and Analytics Officers. The advantages to companies by
year. delegates learned the use of financial governance enabling them to prioritize
their core business functions
In the three-day summit, Gartner proposed new for successful cloud adoption and transitioning while the provider handles
strategies for data and analytics (D&A) leaders towards a unified FinOps approach. data extraction, analysis and
to engage with stakeholders, address skills gaps, Gartner also presented a methodology for D&A utilization. Additionally, these
and provide clear direction for success. Gartner predictions that drive growth, innovation, and services assist companies
discussed using their artificial intelligence (AI) value during uncertainty. They also addressed AI in prioritizing customer
maturity model to foster creative business models, compromise and emerging risks while outlining requirements and improving
weighing the benefits and risks to drive business ways to maximize business value from data. their overall business
value. operations.
Gartner highlighted the role of D&A and AI in Source: Gartner Source: Marketsandmarkets
improving business sustainability. They shared

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 INTERVIEW

Data buddies: bridging the gap

between data analysts and non-
technical team members
INTERVIEWS
DIETMAR BÖHMER
Dietmar Böhmer - Imad Syed - Harry Patria - Jino Noel - Alfonso Medela Chief Analytics Officer
Tyme Group

He joined Tyme seven years ago and he has been leading the data and analytics function across the
group, which includes TymeBank in South Africa and the newly launched GoTyme in the Philippines.
Dietmar has led lending, data science, machine learning, and big data teams in banking for close
to two decades and has lectured in the actuarial field prior to that.

Interview by: Paolo Orduña

Data analytics is a highly-technical field, one that organizations could afford the processing power
requires focus and a dedicated skill set. This begs needed to train the latest AI models. However, with
the question: How can data analysts help non- the help of venture capital, AI development has been
technical team members and stakeholders improve democratized, leading to rapid advancements. As
their data literacy? The answer, according to customers directly engage with AI, comfort levels
Tyme’s Chief Analytics Officer, Dietmar Böhmer, are evolving, and many are willing to engage with
is by having “data buddies.” Dietmar also shares it if it is useful—rather than perfect. The traditional
his insights on how artificial intelligence (AI) and use of AI as an invisible layer for seamless customer
machine learning (ML) are shaping the future of experience is evolving into direct engagement for
banking. both staff and customers.

Perspectives How do you see the impact of recent

What current data-related trends do you developments in AI generative models on the
foresee having the greatest impact on field of data analytics in business?
business? Why?
As mentioned earlier, AI is no longer just an invisible
Cloud computing has revolutionized what’s possible component of businesses that automates backend
Disclaimer: The information and opinions provided by the interviewees with AI and ML. Historically, only government processes, sorts and sifts through data, and
in this section are solely their own and do not reflect the views of The institutions or a few large multinational improves decision-making. Now more than ever,
KPI Institute and Performance Magazine.

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 INTERVIEW INTERVIEW

analytics teams need to empower the rest of the with data, trends, and insights. Creating a safe
business to effectively use AI models. For instance, and open environment where individuals can
custom-tuning their own instance of ChatGPT ask questions without fear is key to fostering the appropriate data and AI governance, and Can you speak to the potential for AI to drive
can provide significant benefits, as seen in many engagement. This also helps the analytics team the capacity to train the board on the latest financial inclusion by giving underserved
successful use cases within our business already. As better understand the business context and avoid capabilities and opportunities of the most communities access to banking services?
people engage with these tools, their expectations drawing spurious conclusions while enabling the rest relevant advancements. Undoubtedly, technology has enabled companies
of the world change. Analytics teams won’t be of the organization to fully grasp how underlying to reach customers, but AI is the critical
immune to this change and will have to evolve trends respond to specific actions or strategies. In your opinion, what is the biggest challenge component that allows them to render services
their reporting and self-service tools to become facing the adoption of AI for data analytics by automating historical hurdles like Know
more conversational, enabling stakeholders to ask Practical Insights within the banking industry? Your Customer (KYC) and AML assessments.
conversational-style questions instead of relying on The primary focus of building and running a Additionally, AI can now automate backend
standard visualizations with limited options to drill bank is to ensure its resilience and readiness. processes to serve customers at the appropriate
down. What are the key skills that a Chief price point. Lastly, AI combined with alternative
Analytics Officer should possess in the The top priority is to enable customers to
always transact across all channels. However, data empowers customers who have historically
context of your role at Tyme? been underserved and are traditionally data-
How can organizations align their data this means many incumbent banks’ banking
strategy with their overall business strategy? Firstly, the ability to embrace and adapt systems weren’t designed to seamlessly embed poor when it comes to the data sources banks
to change is critical, as change is the only AI. Additionally, the highly regulated nature of traditionally use for credit scoring to access
To truly be a data-driven organization, this is credit responsibly.
constant. Secondly, a strategic mindset and the banking industry inherently creates a culture
paramount. The process involves identifying How does Tyme ensure the security and
a strong interest in new developments and of risk aversion, relative to other industries with
business goals, understanding the associated data privacy of the data it collects and analyzes
trends in technology and machine learning less oversight, leading to longer lead times for
needs, developing a fit-for-purpose data strategy, using AI?
are necessary to ensure the organization stays adopting new and disruptive technologies.
and then integrating data into decision-making. By
ahead of the curve. Effective communication Trust is paramount in banking, otherwise,
aligning the data strategy with the overall business
skills are also essential to explain the strategic customers won’t entrust you with their hard-
strategy, organizations can ensure that their data
direction and convey complex data concepts
supports their goals and helps them make informed
and insights to non-technical stakeholders.
decisions that drive business growth and success.
Lastly, a willingness to be hands-on and take
the initiative to get the job done is important
How can data analytics be leveraged to support in a start-up environment where there’s always
and enhance performance management? more work than people available to do it.
This is absolutely key! An organization is only as
good as its measurement and tracking. No matter How do you see AI impacting the banking
what your KPIs are, if they’re not actively being industry in the next five years, and how is
tracked and reported on, then they’ll most likely not Tyme preparing for these changes?
be met. This is really a key part of the data and
The banking industry, like all other industries,
analytics team’s function to empower the business
will be significantly impacted by the rapid
to have clear visibility, measurement, and tracking
advancement of AI. While banks have
in place for all KPIs. As Peter Drucker said, “If you
already been utilizing AI and ML models for
can’t measure it, you can’t manage it.”
credit risk, fraud, Anti-Money Laundering
(AML), and cross-sell optimization, there’s a
How can we support employees to develop and greater focus on customer engagement and
improve their data literacy skills? customer service. AI will play a significant
role in interacting with staff and customers,
To foster a truly data-driven culture, it’s critical unlocking unprecedented opportunities to
to promote data literacy throughout the entire improve the efficiency of staff at all levels. We
organization and not just limit it to the analytics are constantly reviewing our architecture to
team. While classroom training is important, it is ensure that we have the correct data disciples,
not enough on its own. Thus, it is essential to have the ability to ubiquitously consume AI models,
dedicated data buddies from the analytics team
who can provide ongoing support and engagement

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 INTERVIEW INTERVIEW

Key strategies for building a data-

How can organizations align their data How can we support employees to develop and
strategy with their overall business strategy? improve their data literacy skills?
Almost all Fortune 1000 companies already have Different industries have different business
driven culture data and business strategies that are engaged
and aligned with data-driven metrics tied to
functions, so they have different data needs. We
will need to address the challenges of how data will
business KPIs. PiLog has actually been one of support them in:
the pioneers of engaging in major digital and • Reducing mundane, repetitive, and menial
business transformation programs for our existing tasks or processes
customers. We have been promoting data value
management and measuring the positive impact • Reducing errors in business execution
of data for businesses, advocating data as an asset • Becoming part of a new data-driven culture
DR. IMAD SYED with earned value management (EVM). by upskilling and cross-skilling per the business
CEO APAC & ME, Group CIO, and Organizations have to also ensure systematic objectives
Board Member processes and technological adoption, calling for • Enabling and empowering the workforce to
the alignment of strategies to be coupled and make factual, objective, data-driven decisions
PiLog Group
implemented with leadership-sponsored change
In a nutshell, data is the NEW gold or oil. It is so
management.
precious in the world right now and the workforce
needs to start understanding the total impact of
data analytics.

A seasoned technologist, mentor, leader, evangelist, and philanthropist, Dr. Syed worked his way
up to become the CEO of PiLog. His brainchild, PiLog’s Business Technology Platform, focuses on
augmented data management to leverage the latest advancements in tech—such as AI/ML, RPA,
data lakes, data hubs, and big data—for prescriptive analytics.

Interview by: Len Cristobal

How can organizations achieve data maturity and processing, will aid business processability and
ensure value management? Dr. Imad A. Syed, automation. Data management will be augmented
CEO APAC & ME, Group CIO, and Member of as services with multiple cloud deployment options
How can data analytics be leveraged to support
PiLog Group Board, PiLog Group, shares their will provide security and reduce TCO. There will
and enhance performance management?
company’s guiding principles, best practices, and also be a rise in the number of easy-to-use solutions
plans for improving data governance and fostering with improved user interfaces embedded with Data analytics platforms have always been built
a data-driven culture. conversational AI capabilities. to support and enhance business performance
management; some examples are:
Perspectives How do you see the impact of recent • Data-driven analytical footprints for effective,
What current data-related trends do you developments in AI generative models on the real-time decision-making
foresee having the greatest impact on field of data analytics in business?
• Induced, improved, and more realistic
business? Why?
Current data and trends indicate that generative forecasting models for material, asset, and
I see organizations moving away from big data AI is being leveraged on textual, visual, audiovisual, service planning and execution
to small and varied data due to the latter’s and other multimedia technology solutions for
• Results-oriented insights on the organization—
improved processability and analytics. I also see business planning and execution. This trend works
from human capital to operating assets—with
data democratization enabling and augmenting in conjunction with advancements in robotics
correlated benchmarking
processes to provide an improved user experience to enhance design and deployment in various
for better insights and strategies that will drive industries, such as the automobile, defense, • Financial consolidation with benchmarking for
organizational efficiency and effectiveness. Data aerospace, and pharmaceutical industries to name P&L, cost & profit center performance, market
science, AI, and ML, coupled with natural language a few. cap, and even share market speculations.

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 INTERVIEW INTERVIEW

Practical Insights
improved OEE, LCC, and RAM for What are your top principles for developing Can you discuss your role as an innovator of
What is your approach to designing and a data-driven culture for business disruptive technology platforms and share
implementing data lifecycle management organization-run operations with the
greatest reliability transformations and achieving data maturity with us the key competencies that a data
processes? How do you ensure integration for organizations? strategist should possess nowadays?
across various platforms and operational • The establishment of a single version of the
systems? truth with cross-mapping across multiple PiLog’s top principles for ensuring data maturity The key competencies a data strategist should
domains within the organizations has and value management across organizations possess today and in the near future are:
PiLog’s iVision framework and methodology are include:
bundled with standards and procedures from the seamlessly improved visibility across various • Strong industry knowledge bolstered by best
ISO, IEC, UNSPSC, NATO, etc., and embedded functions • Periodic review and updates to metadata practices
in PiLog Business Technology to enable highly parameters with metrics management • An understanding of the impact of master,
scalable workforce management. This keeps How does PiLog ensure that its technical and data structuring for business process meta, transactional, and other data sets on
them simple, modular, loosely coupled, easily dictionary content stays up-to-date and planning, execution, and Control business process planning, execution, control,
integrable, and forward-looking due to continual relevant to the changing needs of its clients • Data-driven metrics tied to business KPIs and reporting/analytics
innovation and improved efforts in automation. in various industries? and KRAs • Championing technology solutions for data
Their compatibility with various combinations
The PiLog technical dictionary and product/ • Improved operational efficiency and modeling, quality, governance, integration,
of operating systems and databases as well
service hierarchies/categories which are effectiveness with technology adoption of migration, orchestration, etc. with empowered
as integration with major ERPs, CRMs, SRMs,
industry-aAgnostic and/or industry-specific are RPA, IoT, IIoT, mobility, AI/ML, etc. automation
COTS solutions, or any third-party integration
kept up to date through partnerships with OEM, • Expertise in data management as
on SOA are either certified or proven to scale in • Implement and improve data governance,
OPM, and OCMs. In addition, investment to prescribed/developed by the ISO, IEC, SOX,
the market. risk, and control to align with ISO and SOX
procure the right data from third-party data DUNS, and other regulatory, compliance,
standards
sources like DUNS, UNSPSC, ISO, etc. and and standards organizations
Can you share or describe a specific success continuous evaluation and updates by internal • Self-aided continual learning and evaluations
story where PiLog's Master Data Quality data engineering and science COE have been • Effective change management for data
• Continuous assessment of the process and
Solutions helped a client save significant part of our research efforts for decades, leading strategy implementation
data orchestration across enterprises using
amounts of money or improve their to the continuous improvement of content to contextualized infographics
operations? ensure that it is relevant and accurate.
With the evolution of PiLog’s value engineering
solutions, data effectiveness and quality are
now measured by the impact of data metrics
on business KPIs and KRAs. Our expertise in
managing data quality parameters (metadata)
has provided immense control over business
process planning and execution, establishing
accurate master data objects across multiple
enterprises. Some of the key use cases include:
• Controlled MRP parameters, Min, Max,
ROP, EOQs, DLT, etc. had shown savings or
cost reductions worth millions of dollars for
our customers managing their inventories.
• Consolidated demand and supply visibility
across a nation or region has provided
significant insights for reducing imports and
increasing opportunities for local investment
• Optimized life cycle management with

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 INTERVIEW INTERVIEW

Practical Insights
How to achieve business goals
How can organizations align their data
strategy with their overall business strategy? Given your accomplishments throughout
Aligning a data strategy with a business strategy your career, can you share or describe a
with data analytics can be a tricky task. To ensure success, an organization
must first establish clear business objectives. Next,
particularly challenging data analytics
project you oversaw, and how you were
they should develop a comprehensive data strategy able to ensure its successful completion?
that aligns with those objectives and provides a One of the toughest projects I ever worked
roadmap for collecting, analyzing, and utilizing on as a people analytics professional was
data. Effective communication and collaboration this social data science thing where we had
between departments are crucial in this process, to create a whole new analytics model from
as well as regularly reassessing and adjusting the scratch. We had to figure out which features
data strategy to align with the business strategy. to use and how to mine the data and deal
with all sorts of crazy stuff, like outliers, class
DR. HARRY PATRIA How can data analytics be leveraged to support imbalance, and collinearity. But we nailed
Founder, CEO, and Chief Data Strategist and enhance performance management? it by improving our feature encoding and
Strategi Transforma Infiniti ~ Patria & Co. making our AI more trustworthy, explainable
Data analytics can be a game-changer when it
and scalable.
comes to performance management. By analyzing
data from various sources—including sales,
marketing, and operations—organizations can gain How have you managed to stay up-to-
valuable insights. They can then use this information date with the latest developments in
He founded a company that serves over 100 corporate clients, 200 analytical platforms, and 500 to set goals, track progress, and make data-driven machine learning and AI, and how do you
professionals. He is a Data Hackathon winner in the UK and graduated with distinction from his decisions to improve performance. Data analytics incorporate these new insights into PT.
Master's degree to Ph.D. program with a fully-funded scholarship. Dr. Patria is a subject matter can also be used to identify trends and patterns Strategi Transforma Infiniti’s operations
expert in several fields. and predict future performance. With the right and services?
tools and strategies in place, data analytics can I stay current in data and AI by pursuing
Interview by: Len Cristobal help organizations stay ahead of the game. three Master's degrees and two PhDs in
strategy, data science, business analytics, and
How can we support employees to develop and engineering from top-ranking universities. We
Being a chief data strategist today requires and marketing. Moreover, applied analytics like
improve their data literacy skills? go beyond boundaries by actively learning,
more than just technical know-how, according to supply chain, energy, and people analytics, along
teaching, researching, and working on projects
Dr. Harry Patria, founder, CEO, and chief data with Bayesian inference, will become more popular. Firstly, organizations should make data literacy
to keep Patria & Co. at the forefront of the
strategist of Strategi Transforma Infiniti ~ Patria Lastly, computational finance will transform a priority and create a culture that values data-
industry. We hire only exceptional talent and
& Co. In this interview, he explains how leadership, financial data analysis. driven decision-making. Providing regular training
create a vibrant ecosystem that fosters a
building trust with customers, and collaboration sessions on data analysis tools and techniques,
continuous learning mindset.
help organizations leverage data to achieve How do you see the impact of recent offering access to relevant data resources, and
business goals. developments in AI generative models on the encouraging employees to practice their data
analysis skills are effective ways to improve data How does your company handle data
Perspectives field of data analytics in business?
literacy. Incentivizing data-driven decision-making quality assurance, and what processes do
What current data-related trends do you Well, recent developments in AI generative models and recognizing employee efforts can also go a you have in place to ensure that data is
foresee having the greatest impact on are set to revolutionize the field of data analytics long way in fostering a data-literate workforce. free of errors and inconsistencies?
business? Why? in business. Businesses can now generate new data
points that were previously unavailable or difficult We take data quality seriously and use a range
In the coming years, several data-related to obtain, allowing for more accurate predictions of tools like outlier detection, feature encoding,
trends will impact businesses significantly. Data and insights. For instance, generative models can and visualization to ensure accuracy. We also
engineering will remain crucial for ensuring the be used to create synthetic data for testing and use fancy stuff like automated exploratory
quality and accuracy of data. Businesses can make training machine learning algorithms, thereby data analysis (EDA), Machine Learning
more informed decisions using explainable AI and reducing the need for large datasets. Additionally,
prescriptive analytics based on actionable insights. generative models have the potential to aid in
Social networks will play a vital role in data analysis anomaly detection, NLP, and computer vision.

16 17
 INTERVIEW INTERVIEW

(ML), Feature Engineering, Explainable AI, and ethical considerations in our use of AI and data Future-forward: using data
analytics in app development
Generative AI and validate data with users, analytics. Ultimately, being socially responsible is
experts, and consultants based on a triangulation not only the right thing to do, but it also leads to
approach. To ensure consistency, we first long-term commercial success by building trust
understand the business process and identify with our customers.
incomplete data sources. Then, we use advanced
multiple imputation by chained equations and What are the key skills that a Chief Data
ensure data visibility to catch any issues. Strategist should possess nowadays?
They should have a deep understanding of
As an industry leader, how do you balance JINO NOEL
statistical, computational and business thinking
the competing demands of commercial
to make sense of data and extract insights Chief Data Officer
success and social responsibility, particularly
that can drive business decisions. But then,
when it comes to data privacy and ethics? Data Analytics Ventures, Inc.
being a Chief Data Strategist requires a broad
It's a tricky balance, but we strive to stay up- skill set that goes beyond just technical know-
to-date with all the latest regulations, like the how. They should have critical thinking and
GDPR and AI Act, to ensure that we are always empathy, effective communication, leadership,
in compliance and protecting our users' data and adaptability. So, yeah, it's not just about
privacy. We also have a team that focuses on crunching numbers anymore. Being a Chief Data
Strategist is a whole different ball game!
He is a data science and technology leader with extensive experience in building data teams and
practices across different organizations. His experience ranges from working in startups to large
conglomerates across both Australia and the Philippines. Jino is currently the Chief Data Officer
at Data Analytics Ventures, Inc (DAVI).

Interview by Paolo Orduña

Data analytics is widely regarded as one of the keep improving their data capabilities, they will want
pillars of informed decision-making. This is quite to start using their models in production systems,
apparent in app development, as explained by which means they will need robust and repeatable
Jino Noel, Chief Data Officer at DAVI. Jino talks processes to guarantee the performance of model
to Performance Magazine about how he and his deployments. Techniques and disciplines from
team used data analytics to glean insights that engineering and operations will be transferred over
influenced the direction they took when developing for this undertaking..
new applications.
How do you see the impact of recent
Perspectives developments in AI generative models on the
What current data-related trends do you field of data analytics in business?
foresee having the greatest impact on I think it’s good that AI generative models have
business? Why? been getting a lot of enthusiastic press coverage
The rise of MLOps is something I see will become lately since this puts AI use cases in the field of
bigger in the near future. Previously, analytics and view of business leaders. This can only spur more
predictive models were used mainly to get insights investment and experimentation by businesses
and were generally run offline. As organizations into AI so they do not get left behind by their
competitors.

18 19
 INTERVIEW INTERVIEW

Practical Insights
How can organizations align their data
strategy with their overall business strategy? What are the key skills that a Chief Data Can you confidently say that DAVI has Can you describe an instance where you were
Officer should possess nowadays? reached data maturity? Why or why not? able to leverage data insights to influence
There needs to be top-level support and acceptance strategic decision-making within DAVI?
of the data strategy. The implementation of a data A Chief Data Officer should have both data- Definitely not, we still have a long way to go.
strategy is a journey, with its own set of trials and related technical expertise as well as people One of our goals this year will be to increase our DAVI operates Go Rewards, the loyalty program
incremental benefits to the overall business strategy leadership skills. Leading will always be part data maturity by improving our data governance of the Gokongwei Group. This includes a mobile
along the way. The benefits should be defined and of the job, particularly for highly specialized management frameworks and practices. This app where users can look at available promos
quantified to make it easier to see how much the technical people such as data engineers would encompass improvements in our data and display their QR codes. DAVI uses analytics
data projects contribute to the business. and data scientists. To be able to lead them catalogs, data lineage, data standardization, to decide the direction of app development, from
properly, I believe it is better to be a technical and automated data quality reports. This all what features to build to how we can improve
person myself, so I can discuss technical goes back to our desire to be able to trust our user engagement. Our recent foray into more
How can data analytics be leveraged to support data and the analytics we are getting out of it. financial-related functionalities such as Go
matters fluently, which helps me gain their
and enhance performance management? Rewards Pay and Go Rewards Loans is a result
trust.
In most companies, employees set their annual of this.
goals and targets, and their performance is What data-related challenges have you
measured against these metrics at the end of the faced as the Chief Data Officer of DAVI?
year. Analytics practices can be used to measure How did you overcome these challenges?
and track their annual performance and also figure
out how to optimize specific aspects of their goals. Our data-related challenges are the same as
Data analytics can also be used to track employee any company. Being able to trust our data,
retention and its drivers to better keep top talent. cleaning up data from our sources, data
latencies, and other related issues. DAVI
overcame these by investing in people—hiring
How can we support employees to develop and high-quality experts in our data engineering,
improve their data literacy skills? data governance, and analytics teams to help
Employees need to be given the freedom to us make sense of the data coming in—and
learn and experiment. We are lucky because data building robust data pipelines which have
analytics is currently one of the most interesting increased the standard of quality of the data
jobs, so people that work in our field are naturally in our data lake.
interested to learn more and improve. At DAVI,
we give our people learning options from different How does DAVI make use of advancements
sources, both online and classroom-based, and we in AI and machine learning to help its
also provide them with the opportunity to test what clients understand their customers’ needs
they learn in their work projects. and buying patterns?
DAVI has recently started using machine
learning to model our users’ propensity to
buy certain products. This helps us create
more accurate target audiences for our
precision marketing campaigns. We are also
moving forward with a recommendation
engine project, with the goal of improving
user engagement with our retail partners and
with our promos and campaigns. On top of
this, we are improving our machine learning
operations expertise to make our model
deployments repeatable and robust.

20 21
 INTERVIEW

Beyond skin-deep: leveraging AI

eLearning to improve diagnostics accuracy
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for skin pathologies
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v 1.0 2023 Performance Magazine how he spearheaded the that use a lot of data.
development of algorithms that are designed to
identify skin pathologies and also discusses how his How do you see the impact of recent
team handles sensitive patient data. developments in AI generative models on the
Certified Performance Management Systems Audit Professional
– Online Course Perspectives field of data analytics in business?
Generative models offer potential improvements
What current data-related trends do you
across various fields, but caution is required in
foresee having the greatest impact on
healthcare to minimize risks. General adversarial
business? Why?
Start your eLearning journey today networks (GANs), a type of generative model, create
I think that there are three important things that synthetic images like skin moles and cancers for
will greatly impact businesses: AI, data safety, training purposes. However, GANs can occasionally
and edge computing. AI helps us find useful produce inaccurate images. Alternatively, Natural
kpiinstitute.org/education/elearning/ T: +61 3 9028 2223 M: +61 4 2456 8088 information, perform tasks automatically, and Language Processing (NLP) models may prove
make better decisions. Data safety is important more beneficial for healthcare applications.

22 23
 INTERVIEW INTERVIEW

How can organizations align their data Practical Insights

strategy with their overall business strategy? .What approaches or methodologies do you Skin pathology diagnosis and therapies
What are the key skills that a Chief use to ensure the accuracy and reliability of often involve sensitive patient data. How
Organizations can enhance their respective
Artificial Intelligence Officer should computer vision algorithms in the context do you approach data privacy and security
business strategies by identifying primary goals,
possess in the context of your role at of skin pathology diagnosis? Can you share concerns in the development and deployment
determining crucial data, and focusing on data-
Legit.Health? examples of how you have validated the of computer vision technology?
driven projects. This involves using data for
A Chief AI Officer at a medical organization performance of AI models and ensured their Addressing data privacy and security concerns
decision-making, fostering a data-centric culture,
like Legit.Health needs strong AI expertise, safety and effectiveness in real-world clinical is of the utmost importance in the development
and investing in quality data systems, tools, and
including extensive knowledge of machine and settings? and deployment of AI algorithms in healthcare.
training. Regularly updating the data plan as the
business and technology evolve ensures seamless deep learning, and a profound understanding To guarantee accuracy and reliability, our We adhere to strict data protection regulations
synchronization and effective collaboration. of medical data and healthcare to ensure computer vision algorithms undergo a multi-stage like the General Data Protection Regulation
precise algorithm development. Besides validation process that encompasses retrospective and HIPAA, incorporating data encryption
technical skills, strategic thinking and and prospective clinical validations. Rigorous and anonymization techniques. Additionally, we
How can data analytics be leveraged to support
leadership are vital for guiding the AI team testing is performed on diverse, representative implement role-based access controls, rigorous
and enhance performance management?
and aligning with company goals. Great datasets, employing cross-validation to assess auditing, and continuous monitoring to ensure
Data analytics enhances employee management communication and collaboration skills model performance. We collaborate closely with data integrity. Our commitment to privacy-by-
by providing insights into performance, identifying are also crucial for working effectively with medical professionals, reviewing AI model outputs design principles ensures that data protection is
areas for improvement, and setting fact-based different teams. and gathering feedback to iteratively refine our integrated throughout the development lifecycle,
goals. Managers evaluate productivity, teamwork, algorithms. Furthermore, we conduct clinical fostering a secure and trustworthy environment
and industry benchmarks to better understand trials and pilot studies to evaluate safety and for sensitive patient information.
individual and team performance. Data analytics Can you describe your experience
efficacy. This ensures that our models adhere to
helps in this endeavor by making it easier to predict in developing and implementing
real-world requirements and actively contribute
skill gaps and suggest appropriate training. Real- AI strategies for computer vision
to enhancing patient outcomes.
time performance tracking enables swift feedback applications, specifically in the context of
and adjustments, fostering a work culture that diagnosing and treating skin pathologies?
continually strives for improvement. How have you leveraged AI to improve
diagnosis accuracy and enable life-saving
therapies?
How can we support employees to develop and
improve their data literacy skills? Heading a team of specialists, we've developed
advanced algorithms that accurately identify
To help workers get better with data, companies 232+ skin conditions and automate follow-
can offer special classes, workshops, and online ups for chronic skin conditions. Using deep
lessons. Organizations should make learning a learning techniques, our platform provides
regular thing and share knowledge. To accomplish real-time diagnostic support to healthcare
this, they should set up programs where people professionals, improving their accuracy and
help each other, and give them tools and projects enabling early intervention. By collaborating
to practice on. It’s also important to celebrate their with medical experts and continuously refining
growth and create a friendly place where they can our algorithms, we are able to offer a powerful
ask questions and learn together. tool that empowers clinicians, transforming
healthcare and improving patient outcomes.

24 25
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 COVER STORY COVER STORY

during these processes can have a profound impact language models (LLMs), foundational models,
on the organization. Meanwhile, data modeling and conversational models—in the business

Strength in numbers: embracing

should be quickly deployed for business processes landscape. He is hopeful about the future, stating
where user behavior and action require facilitation that “the realization of big data infrastructures,
and substantiation. the generation of huge volumes of data, and the

dynamic data strategies for business availability of cost-effective compute and storage
have made way for endless possibilities.” He notes

transformation
that these developments have allowed for the
“reimagining [of] business processes from scratch
and created new business models and new markets
for companies.”

Mayank also points out the emergence of a new

wave of digital tools that leverage generative AI to
provide end users with a personalized experience
along with unrivaled flexibility and customizability
He warns companies that there is an inevitable
disruption in traditional analytics tools that use
rules-based frameworks, but this can be avoided
by pivoting and adopting new technology, such as
Madhur Mayank Sharma, Senior Director and generative AI.
Senior Director and Head of Artificial Intelligence (AI) Development at SAP Head of AI Development at SAP
Asia PTE LTD Madhur Mayank Sharma shared in an interview with Performance Businesses can look no further than the current
Magazine his insights and expertise on developing an effective, forward-thinking On performance management state of AI development in Asia and the Pacific to
data strategy. Data analytics is widely regarded as an excellent see how these advancements are making waves.
tool to support and enhance performance The region presents a unique set of challenges as
Paolo Orduña management. This is nowhere more apparent well as opportunities in the adoption of AI products
than in its utility when it comes to establishing and services. Mayank explained that, on one hand,
key performance indicators (KPIs). Mayank says, the ever-changing nature of the region’s business
Data analytics forms the bedrock of informed
decision-making. It is an essential aspect of On strategy “Having the right data infrastructure, along with landscape coupled with multiple language barriers
goal-driven data modeling, allows businesses to and varied business processes can make it difficult
strategy, enabling organizations to recognize gaps In an interview with Performance Magazine, for AI systems, particularly LLMs, to achieve their
establish relevant KPIs.”
and patterns that might otherwise go unnoticed. Mayank emphasized the importance of establishing desired results. On the other hand, many companies
In an increasingly data-driven world, analytics clear business objectives, which will help identify
Once these relevant KPIs are identified, they can in this region are willing to experiment and are
is quickly—and deservedly—getting its time in relevant data points and data quality. Once that
be compared to a business’s historical performance open to change, ushering in innovation.
the limelight. Thus, it is absolutely critical for an has been done, it is time to choose the right data
trends to “establish relevant goals, measure
organization to have a sound data strategy that platform to facilitate the creation of the required
ongoing performance, forecast performance trends, Looking to the future, Mayank remarked about
can adapt to the never-ending march of progress. digital infrastructure. “This infrastructure should
implement course correction in the event of deviation new skills poised to be in high demand. “With the
One person who knows this all too well is Madhur support seamless and real-time data flow from
from goals, and strongly position themselves to emergence of generative AI, prompt engineering
Mayank Sharma, Senior Director and Head of the source of generation to the point of decision- is another field that will become essential for
meet business objectives,” per Mayank.
AI Development at SAP. making,” he said. everyone to learn. Prompt engineering skills in the
For all of this to work, companies must establish data analytics space can enable users to derive
An engineering leader with over 17 years of Real-time data flow enables quick and agile
a culture of data-driven decision-making. Mayank insights from data quickly and efficiently.”
experience in the enterprise software industry, strategic adjustments, granting organizations
urges organizations to invest in data infrastructure,
Mayank oversees SAP’s AI unit in Singapore, more flexibility in terms of planning and execution.
data modeling, data governance, data quality, and Data analytics is expected to keep evolving at
leading the development, market introduction, However, speed and agility must be balanced with a rapid pace alongside AI and ML. Therefore,
their overall data strategy.
and adoption of numerous AI applications. His accuracy and rigor, particularly in data modeling it is now more important than ever to develop a
position and experience have granted him a deep and interpretation. Mayank believes that this dynamic data strategy—one that is continuously
understanding of what it takes to create a robust balance has to be established on a case-by-case On trends and trajectories monitored and improved to sustain an upward
and dynamic data strategy. basis. For critical business functions, accuracy takes Mayank also discussed the growing prominence trend in business performance.
precedence over speed because decisions made of data-related trends—e.g. generative AI, large
28 29
 IN-DEPTH

STRATEGY PLANNING

Sustainable strategy in focus:

leveraging data to reduce
environmental footprint
Liana Paraschiv

Constant progress in data-driven policy-making cover 16 environmental impacts, including climate

moved the emphasis from reactive responses change and impacts related to water, air, resources,
to natural disasters toward more analysis of land use, and toxicity.
environmental dynamics. Environmental data

IN-DEPTH
measurement and analysis are essential, as the From a company's perspective, there is significant
results highlight where companies can act to potential in reducing the environmental footprint all
improve their operations. Also, by monitoring along the value chain: in research and development,
environmental data at regular intervals, they can procurement, production, distribution, consumption,
compare and analyze changes. and/or disposal. Procurement principles could be
changed and procedures could be primarily for
The environmental footprint is an emerging set reuse, the chemicals used could be changed to
of notions; the label “footprint” comes from the eco-chemicals, and labeled waste such as food,
notion of the mark made on the surface. Europe paper, plastic, and metals could be systematically
Strategy Planning - Strategy Execution - Performance
has recently defined a standard methodology, recycled. Electrolux Group, one of the most
Measurement - Data Analytics
and the European Commission adopted a revised prominent household appliance companies in the
Recommendation on the use of Environmental world, developed a value chain perspective on
Footprint methods in 2021. The Environmental sustainability (see Figure 1) that helps identify
Footprint methods measure and communicate potential, minimize or enhance impacts, and
the environmental performance of products and understand boundaries.
organizations across their whole lifecycle. They
30 31
 IN-DEPTH IN-DEPTH

Strategic area within Initiatives and goals achieved in Impact Transport • 35% of annual ocean cargo was Medium
More CO2 is emitted transported using more sustainable fuels.
the value chain 2022
transporting Electrolux
goods than through the
total operational energy
use.
Product development • Improved the energy efficiency of High
Close collaboration between Electrolux’s global product offering by over
design, marketing, and R&D 1% on average in 2022. Sales and Consumer use • Refrigerator solutions such as Cooling High
enables new products to • KPIs on energy efficiency were further Energy and performance 360 and ColdSense that make ingredients
offer best-in-class consumer integrated into product planning. labeling along last longer and help reduce food waste
experiences, leading to • In 2022, resource-efficient products with sustainability were introduced.
improved environmental accounted for 24% of total units sold but communication raised • A new washing machine model, Care
performance. 39% of gross profit. consumer awareness Drum, was combined with enhanced cycle
• Electrolux front-load washers in North of resource and functionality to reduce wear and tear on
America save an average of over 450 product efficiency. garments.
liters (120 gallons) of water per year As the main environmental • A microplastic filter was used to capture
compared to top-load washers. impacts of products occur microplastics to avoid them ending up in
• The PURE 4X water filter in Latin during their use, product wastewater systems and potentially the
America saves 3,000 plastic liter bottles energy and water efficiency environment.
per filter. In addition, it has a new slimmer are top priorities • Electrolux removed chemical paint
shape that reduces the amount of plastic from the stick vacuum cleaner to reduce
in the product by 27%, which also reduces environmental impact.
packaging waste. • Electrolux introduced more sustainable
packaging that incorporates more recycled
materials and reduces overall environmental
impact.
Suppliers • Sustainability performance was Medium
Working with suppliers integrated into purchasing and sourcing
safeguards Electrolux’s decisions. End-of-life • In Europe, where the most comprehensive Medium
standards and develops • 35% of annual ocean cargo was Legislation on appliance producer responsibility legislation exists,
supplier capacities to further transported using more sustainable fuels. recycling is increasingly 80% of the materials (by total volume)
improve sustainability being introduced into collected from large appliances must be
performance. markets, and Electrolux recovered (70% for small appliances).
market research indicates • In Brazil, a recycling system for electronic
that recycling is a top waste with producer responsibility has been
Group • There was an 82% reduction in carbon Medium priority for consumers. introduced.
operations emissions for scopes 1 and 2* (2015 baseline),
Electrolux worked to reduce surpassing the 2025 science-based climate
the environmental footprint target.
of operations, maintain • 98% of electricity came from renewable Figure 1. Strategic initiatives and goals to support Electrolux's sustainability framework | Source: Electrolux Group, 2022
high ethical standards and sources.
working conditions, and
create a positive impact in *scope - 1 Direct GreenHouse Gases (GHG)
local communities. emissions, (emissions are released into the
atmosphere as a direct result of activities)
scope - 2 Energy indirect GreenHouse Gases
(GHG) emissions (from the generation of
purchased energy from a utility provider).

32 33
 IN-DEPTH IN-DEPTH

Data analysis followed by innovation helps UK, and US, per the World Economic Forum. This STRATEGY EXECUTION
businesses optimize their use of resources, and there will translate into the integration of ESG reporting

Business simulation: a revolutionary

is significant potential, especially for the resources with a company’s financial reporting.
that are intensively used, such as water. According
to WWF, water scarcity around the world is an A systemic perspective is needed to support
increasing issue, with a total of 2.7 billion people
finding water scarce for at least one month of the
decisions that have effects on the environmental,
social, and economic spheres in which the concept solution for organizations
year. of sustainability is articulated as the “development
that meets the needs of the present without Andreana Dumitrescu
Here are two examples from Electrolux Group that compromising the ability of future generations to
highlight the potential of new technologies which meet their own needs,” according to the World
can help reduce environmental impact: unique Commission on Environment and Development.
washing machine compartments to ensure that This is a holistic approach from a data perspective
every type of detergent properly dissolves for short as well, as it brings together various types of data.
washes, and power jet technologies that combine Strong data collection, environmental data analysis,
water recirculation with reduced mechanical and data management capabilities play a key
agitation to save up to 50 liters of water per cycle. role in ensuring a successful implementation. The
New York University Stern Center for Sustainable
As pressure on environmental objectives increases, Business states that these types of initiatives will
companies that realize benefits while meeting drive financial performance due to factors such as
sustainable goals are at an advantage since improved risk management, increased innovation,
corporate Environmental, Social, and Governance and enhanced reputation and relations with clients,
(ESG) disclosures will become mandatory given employees, and investors.
new governmental efforts in the European Union,

A business simulation is an experiential learning Business simulations use various elements of

activity that mimics real-world business scenarios gamification, such as points, badges, and
to allow employees to practice decision-making leaderboards, to engage players and make
and problem-solving skills through games in a learning more enjoyable. Rather than simply
safe and risk-free environment, per Forbes. These memorizing information, participants must analyze
simulations are the successors of video games, data, solve problems, and make decisions together.
which were created in the 1950s, when computers The simulation reacts to player choices, offering
were only accessible to a few large organizations immediate feedback and enabling participants to
and universities, according to the Smithsonian improve their overall abilities. As reported by The
educational platform. Welding Institute, every process or system involving
a flow of events can be simulated.
One of the earliest examples of a business sim, IBM’s
Sumerian Game, was a rudimentary text-based Scientists demonstrated that people learn better
game that focused on economic management in from personal experiences, and this is exactly what
an ancient city. It was designed by Mabel Addis, a business simulation offers to the organizational
a teacher, and programmed by William McKay, environment in practice, according to the Celemi
an IBM employee. Nowadays, business simulations learning platform. By adding gamification elements
have evolved to incorporate advanced graphics, like competition, rewards, and feedback, the
virtual reality, and artificial intelligence to create simulation can motivate employees to work harder
immersive simulations that reflect current business and achieve their goals (see Figure 1).
environments, allowing organizations to customize
them according to their needs.
34 35
 IN-DEPTH IN-DEPTH

Industry Simulation Game Description Scope

• Simulate real-life experiences This allows employees to gain hands-on knowledge of
tools and systems, leading to deeper and more sustained Factory Planner "Plan a manufacturing "Planning material
in a safe environment development through relatable experiential learning. plant for high-voltage flows, monitoring,
cable production" ramp-up support,
reacting to events"
• Drive optimal knowledge Experiential learning improves knowledge retention, develops Manufacturing Littlefield Technologies "Manufacturing of "Equipment utilization,
a more capable team, and creates an understanding of digital satellite queuing, scheduling,
retention over time context, resulting in cost-effective and efficient training.
systems" forecasting"

SAP ERPsim "Manufacturing "Inventories, material

Simulations provide immediate and insightful feedback, company in a ordering, production,
• Gain immediate and insightful
leading to effective learning and skill adaptation.
feedback competitive market" downstream logistics"

"Automobile Supply "Supply chain of Supply chain network

Chain Management automobile design and
This is done by lowering hesitation and fostering a more (AUSUM)" manufacturer" management,
• Minimize the risk and fear
open approach to making mistakes and learning from them.
of employees inventories, logistics
Supply Chain "Beer Game and its "Beer production and "Order processing as a
improved versions" distribution" factory, distributor,
wholesaler or retailer"
Simulations can provide real-time data analysis and reporting
• Ensure that data is accessible, for HR departments and managers while enabling employees
quantifiable, and measurable "Global Supply Chain "Supply chain of "Forecasting, managing
to track their own development, leading to a more holistic
Management" mobile phones" suppliers"
approach to management.

Figure 1. Advantages of using simulations for organizations | Source: Adapted from Industry Today 2020 Article Figure 2. Top manufacturing and supply chains simulations | Source: Adapted from Roland Schmuck 2021 Article

Some of the top industries where business stakeholders deal with production planning, A popular business simulation is MIT’s Beer Game from individual mistakes. Surprisingly, it is used
simulation games have become a common practice inventory, and cost control. The simulations (see Figure 3), which already offers training to in a broad range of industries where physical
and proved their benefits are supply chain and accomplish this by teaching players how their thousands of people around the world about the products or supply chains aren’t present, such as
manufacturing, according to a Roland Schmuck organizations can generate a higher profit using structure and dynamics of supply chains. Its final finance, services, and government. The success of
2021 study (see Figure 2). Based on 22 simulations, forecasting and scheduling methods along with goal is to minimize total inventory and backorder this game is indicated by its constant updates and
the study explains that their main role is to correct stock and lot-sizing decisions. costs by teaching players that most problems new versions, illustrating the high interest shown by
the most common issues of these industries, helping result from a poorly organized system and not organizations for this learning method.

For all entities, gamified training can be considered

an efficient learning instrument as it comes with
many advantages, such as creating a pool of
talented leaders, accelerating strategic change
initiatives, improving engagement, and enabling
employees to have a meaningful learning
experience. While organizational training needs
must be chosen according to each industry, they
don’t need to be dull, and with the constantly
evolving nature of business environments, there is
no excuse not to incorporate entertainment into the
Figure 3. Image from Beer Game | Source: Adapted from
Zensimu 2023 simulation platform
learning and development process.

36 37
 IN-DEPTH

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One of the most common challenges faced intended uses in operations, decision making, and
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(see Figure 1).
This is particularly important as the collected data
is expected to be of high quality and "fit for their
office@kpiinstitute.org smartkpis.com T: +61 3 9028 2223 M: +61 4 2456 8088

38 39
 IN-DEPTH IN-DEPTH

Recognizing and overcoming data audit, several faulty elements have been identified,
revealing potential inaccuracies that could have an
quality hurdles adverse impact. This section presents approaches
for effectively resolving these faulty elements to
Figure 2 highlights a dataset that has encountered
improve data reliability.
significant data quality issues. Through an initial

Figure 2. Sample quality troubled dataset | Source: The KPI Institute

A - Completeness: There is a missing value in the Communicating these deadlines to all relevant
Actual Result column. One way to prevent this is to parties and sending reminders for data submission
Figure 1. Data Quality Dimensions | Source: Certified KPI Professional training program develop and utilize a data collection template that can also help address this issue.
clearly outlines the necessary data fields. It is also
important to regularly review the completeness D - Conformity: The KPI is expressed as a percentage
of the data and address missing information that rate, but the data provided for the result includes a
Data Quality Dimensions – Definition of Terms affects analysis. numerical value. To ensure conformity, organizations
must provide clear guidelines on data format and
1. Accuracy is the extent to which data is error- 4. Consistency indicates whether data is B - Consistency: The structure of the data does not how the KPI should be calculated.
free and reflects on the realities measured. synchronized across different sources or time correspond with the template, the name, and the
periods, and consistent in terms of meaning position of the Data Custodian being switched. To E - Accuracy: This issue concerns the usage of an
2. Timeliness indicates whether the data was and structure. prevent this issue, one must make sure the data inappropriate sign. The KPI measures a rate, but
submitted within the data gathering and presents the same values across different systems the sign used in the KPI name is “$.” To ensure
reporting deadline, and how up-to-date the 5. Conformity ensures data follows specific and follows the same structure. accuracy, one should make sure the data reflects
data is for the task at hand. standards and guidelines, including adherence real information, including the use of appropriate
to a requested format. C - Timeliness: This issue pertains to the data being units. To adhere to accuracy, The KPI Institute
3. Completeness refers to the degree to which received after the specified deadline. One potential developed a naming standard, which designates
data is complete and contains all the required 6. Uniqueness measures the degree to which solution is to establish a data collection cycle the symbols ”#” for units, ”%” for rates, and ”$”
information. data records are uniquely identifiable and not time and set clear deadlines for data submission. specifically for monetary value.
duplicated.

40 41
 IN-DEPTH

Reliable data drives effective KPIs of forecasts, leading to missed opportunities. In

Maintaining data quality is essential to generate
addition, it can hold back innovation, causing
businesses to lose competitiveness.
Micro-credentials in Maturity Assessments
meaningful and effective KPIs. Reliable data ensures
that business decisions are based on trustworthy
Therefore, it is recommended that organizations
information, resulting in improved marketing, A micro-certification is a niche course, targeting the development of one skill or competency in a
prioritize data quality management and take
increased customer satisfaction, enhanced internal specific area of expertise. These training courses offered by The KPI Institute are different from its
actions to assess and improve data quality to
processes, and reduced costs. Certifications Programs from several perspectives:
enhance KPIs and drive business success.
On the other hand, unreliable data can cause • No pre-course and post-course assignments;
Enhance your understanding of KPIs and explore
significant challenges. KPIs based on inaccurate • Shorter course duration;
how reliable data fuels their success by signing up
data lead to wrong decisions, resulting in • No Certification Exam;
for The KPI Institute’s Certified KPI Professional
wasted resources and a negative impact on the • The micro-credentials obtained can be used when enrolling to a Certification Program in our
and Practitioner course.
organization's performance. Poor data quality can portfolio.
impede the identification of trends or the accuracy
IFICATE
Certificate in Strategic Planning Maturity Assessment
RT IN
CE
STRATEGIC
PLANNING
This course will help professionals identify the weaknesses and strengths of
PERFORMANCE AUDIT
strategy planning frameworks using a maturity model assessment. Participants

C-PA
will develop the necessary skills to act as advisors for improving strategy
Performance Maturity

MA

T
Model Framework

EN
v 1.0 2020
U

T
formulation practices in organizations.
RI M
T Y A SSESS

Certificate in Performance Measurement Maturity Assessment IFICATE

RT IN
CE
PERFORMANCE
The micro-certification is focused on building the skills to assess KPI usage MEASUREMENT

practices and enhance the performance measurement framework in PERFORMANCE AUDIT

C-PA
organizations. Professionals will be able to conduct a maturity assessment and
Performance Maturity

MA

T
Model Framework

EN
v 1.0 2020
U

T
propose improvement recommendations.
RI M
T Y A SSESS

Certificate in Performance Improvement Maturity Assessment

IFICATE
RT IN
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This training course looks into the assessment of processes specific to
PERFORMANCE
IMPROVEMENT

PERFORMANCE AUDIT strategy execution like performance reporting, decision-making and initiatives

C-PA
Performance Maturity
management. The learning experience is developed around a performance

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Model Framework

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management maturity model, which managers will get to use to identify the
U

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maturity of their practices and the best ways to move forward.

Certificate in Employee Performance Management Maturity Assessment IFICATE

RT IN
CE EMPLOYEE

Human Resources Specialists involved in managing employee performance will

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find this training useful as it captures the specific characteristics of Employee PERFORMANCE AUDIT

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Performance Management Systems on a 5-level maturity scale. Professionals
Performance Maturity

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Model Framework

EN
v 1.0 2020
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will be able to drive changes in current employee performance review practices
RI M
T Y A SSESS

by developing explicit roadmaps for improvement.

For more details and inquiries, contact Cristina Mihăiloaie,

Business Unit Manager – Research Division:

cristina.mihailoaie@kpiinstitute.com T: +61 390 282 223 or +40 749 424 517

42 43
 IN-DEPTH IN-DEPTH

DATA ANALYTICS

Beyond the hype: How can businesses

adopt technologies that matter?
Peak of Inflated Expectations

Islam Salahuddin Plateau of Productivity

Slope of Enlightenment

Trough of Disillusionment

Technology Trigger

Figure 1. Gartner’s Hype Cycle | Source: Gartner and Wikimedia

1. During the Innovation Trigger phase, the technology adoption should address one or more
technology is not yet sufficiently investigated. of the existing business objectives. Starting from the
While this is a suitable phase for experimentation business strategy and finding the most beneficial
with the new technology, it is not the proper technology adoption is a good start. But this is still
time for full investment and final adoption. not enough.
2. During the Peak of Inflated Expectations,
cautiousness should be at its maximum level Because new technologies can create new business
because this is when most of the promises made objectives and lead to strategy reformulation, it is
will turn out to be false or inaccurate. also essential to go through an iterative process
3. In the Trough of Disillusionment, it is crucial to of reviewing the strategy according to emergent
absorb the critiques that arise and move to an technologies that are potentially useful. Going back
“Technology changes exponentially (fast), yet Yet, not all new technologies are created equal. agile adoption according to the results of initial and forth between potentially useful technologies to
organizations change logarithmically (slow).” Some take the buzz and vanish, and others stay testing combined with the monitored critiques. the business strategy is how a business can be led
This statement is known as Martec’s Law, which around and make a real impact. Chasing every 4. The Slope of Enlightenment is the suitable phase by technology. Combining both enablement and
highlights the importance of keeping an eye on new technology can be disorienting, and can be for organizations to escalate the adoption of leading functions of technology within a business
emerging technologies and adopting only the ones just as catastrophic for organizations as lagging new technology and enhance its applications in is crucial and can only be achieved within agile
with real benefits to businesses. behind. So, how can organizations determine which business. management systems.
are the ones that come with real benefits? 5. Before the technology rests on the Plateau of
But the hype that comes with new technologies Productivity, it should have had a clear resting
By adjusting the level of cautiousness according to
leads to a sense of urgency to catch up with the First, they should be aware of the emerging role in the business. the hype cycle phase and combining the enablement
race. The pressure to adopt new technologies can technology and recognize its hype cycle phase. and leading functions of technology, organizations
be felt with the advancements of large language Created by Gartner, the Hype Cycle (see Figure 1) Running through the previous steps with every can cut through the hype and identify technologies
models (LLMs) like ChatGPT. This was fueled is a graphical representation of hype that consists new technology can still be distracting and time- that will add real value to their operations, staying
by successive hype over the last few years over of five phases. Once an organization identifies a consuming. To decide which ones are worthy ahead of the curve and remaining competitive in
technologies such as blockchains, NFTs, augmented new piece of technology’s current hype phase, it of business resources, an organization should an increasingly tech-driven world.
reality (AR), and the Internet of Things (IoT). should adjust its level of cautiousness accordingly. be oriented toward strategy. Each potential

44 45
 IN-DEPTH

Gartner Hype Cycle Phases Summary

• Innovation Trigger: A potential • Slope of Enlightenment: More instances

technology breakthrough kicks things off. of how the technology can benefit the
Early proof-of-concept stories and media enterprise start to crystallize and become
interest trigger significant publicity. Often more widely understood. Second- and
no usable products exist and commercial third-generation products appear from
viability is unproven. technology providers. More enterprises
fund pilots; conservative companies remain
• Peak of Inflated Expectations: Early cautious.
publicity produces a number of success
stories — often accompanied by scores • Plateau of Productivity: Mainstream
of failures. Some companies take action; adoption starts to take off. Criteria for
many do not. assessing provider viability are more clearly
defined. The technology's broad market
• Trough of Disillusionment: Interest wanes applicability and relevance are clearly
as experiments and implementations fail paying off.
to deliver. Producers of the technology
shake out or fail. Investments continue
only if the surviving providers improve
their products to the satisfaction of early
adopters.

PERFORMANCE
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Data Literacy - Data Culture - Data analytics KPIs

46 47
 ASK OUR EXPERTS ASK OUR EXPERTS
positions like data translators. Making room at media and attending conferences, managers and
the management tables for data-experienced executives can find out in real-time the challenges
managers and chief officers will bridge the gap other leaders face, discuss them, and take on new
more easily. ideas for implementation as early as the next day.
These communities of managers and executives
From a big-picture perspective, developing a wider are valuable assets in today’s challenging business
data culture environment within an organization environment.
can eliminate such gaps on different levels. Business
data maturity can only be achieved if business

Ask Our Ask Our

objectives are aligned with and then enabled by
data uses, which highlights the importance of
crafting a data strategy in alignment with the Roxana Barb
Head of Educational

Experts Experts
overall business strategy.
Programs
The KPI Institute

Islam
Salahuddin
Send your questions to performance@kpiinstitute.org Data Analyst Send your questions to performance@kpiinstitute.org
The KPI Institute

Q: How can organizations bridge

the knowledge gap between Q: How can managers and
executives stay up-to-date with About the Expert
data analysts and non- the latest advancements in data
technical stakeholders and analytics? • An education, management and publishing
decision-makers? A: The field of data analytics is very important
professional with more than 12 years of

A:
combined experience
nowadays, considering how the business environment
Bridging the gap between data teams and About the Expert is going through continuous developments in • Skilled at using Predictive Analytics
non-technical stakeholders should be a multi-way terms of technology, innovation, globalization and Software (PASW), Microsoft Visual Fox,
effort. • A data analyst with a strong focus on sustainability. The field also faces various economic Google Adwords Editor and Adobe
storytelling and data visualization, growing struggles and unexpected challenges. For these FrameMaker
From the technical side, data analysts first have statistical knowledge and a developing set reasons, managers and executives must remain up-
to be aware of business needs and then adopt of technical skills and tools to-date with information and data to make the best • Experience in quality control, marketing,
communication best practices. Insights should be decisions for their organizations and maintain their and process improvement
delivered in the plain language of stakeholders, • As a specialist in data analysis at The KPI competitive advantage in the market by creating
eliminating technical jargon and providing business Institute, Islam leads the generation of value for clients. • Master's degree in Strategies and Policies
context. Data storytelling techniques should be research on the domain of data analytics of Management and Marketing at “Lucian
leveraged to ensure communication is engaging and the development of business analytics To do so, I recommend managers and executives Blaga” University, Romania
and persuasive. toolkits join different professional groups on LinkedIn where
• Currently taking Ph.D. in Management at
• A former research analyst at Frontier they can ask questions and discuss any challenges
From the side of stakeholders, having a high level “Lucian Blaga” University, Romania
MEA Ltd, in charge of data gathering they are facing. They should also have subscriptions
of data literacy is key to avoiding communication and introducing data analysis pieces to various research journals and business magazines.
gaps and insight misinterpretations that can lead • Marketing Diploma Digital HR (Best
It also helps to attend conferences where they can
to distorted decision-making. • Worked as a junior data analyst at Smart Consulting, issued in May 2022)
meet researchers and professionals from both the
InfoTimes, performing data scraping, academic and business worlds. • Process Improvement Manager, Business
Moreover, as hierarchical organizational gaps analysis, and data visualization and
Administration and Management
widen in larger businesses, having mediator roles producing data-driven pieces in both Furthermore, following business blogs, watching (USAMV Bucharest, issued in October
can also be beneficial. These roles can be performed Arabic and English podcasts, and reading books are valuable methods 2019)
by experienced business analysts or specialized to gather new data to make informed decisions.
By being part of professional groups on social

48 49
 ASK OUR EXPERTS

products to the market.

• % Market Share: By understanding and
analyzing the causes behind our market share,
we can further analyze customer preferences,
competitor offerings, and market trends.

Those are some of the important KPIs that will

help organizations to assess their data analysis

Ask Our
initiatives and identify new data analysis initiatives
which will allow management to make informed
decisions about resource allocation and operational

Experts
improvements, and focus on their return on
investment. Finally, we should always remember
that measuring the return of any initiative depends
on its main objectives, which may vary between
them.

Send your questions to performance@kpiinstitute.org

Send your questions to performance@kpiinstitute.org
Fadi Al-Jafari
Q: What are the most important
KPIs for measuring the ROI of
Senior Management
Consultant
data analytics initiatives? The KPI Institute

A: It is crucial to identify and measure the most

relevant KPIs to measure the return on investment
(ROI) of data analysis initiatives. The KPIs may vary
depending on the objectives of each initiative, there
are some common ones that can be used in almost
all initiatives to provide valuable insights. Here are
the KPIs for measuring the ROI of data analysis
initiatives:
• $ Revenue: It helps identify new revenue About the Expert
opportunities by targeting new markets, • A management consultant who has been
developing new products or services, or involved in multiple projects related to
optimizing pricing strategies. designing, implementing, and auditing
• $ Costs Reduction: It helps the business identify Performance Management Systems

CAREER
areas where it can save money, such as
optimizing the supply chain, reducing waste, or • Certified Strategy Business Planning
improving resource allocation. Professional, Certified KPI Professional
• # Customer Satisfaction: Measuring and and Practitioner, Certified Performance

INSIGHTS
observing customer behavior, preferences, and Management Professional, Certified
needs, leads to improvement in our operations Employee Performance Management
and customer service experience. Professional, Certified BSC Professional,
Certified Data Analysis Professional, and
In addition to the previous examples, I also suggest Certified Data Visualization Professional in
measuring some KPIs that are relevant to how the both Arabic and English
company deals with the market and its customers: • Master's degree, MBA Management at
Data Analytics Courses - Recommended Resources
• # Time to Market: Helps identify bottlenecks in German Jordanian University
the time it takes to introduce new services or

50 51
 CAREER INSIGHTS CAREER INSIGHTS

ARTICLE how marginal statistical foundation can be in job That is why The KPI Institute’s Certified Data

Overlooking statistics in data analytics

descriptions compared to the tempting names of Analysis course provides a balance between
coding tools like SQL, Python, R, and others. It is theoretical and practical application, ensuring that
a well-known inside joke that many professionals data professionals develop a deep understanding
courses: a dangerous mistake get amused by such tools while applying for jobs
only to find in the end that Excel is what all the job
of statistical concepts while gaining hands-
on experience with essential tools. It prioritizes
requires when they get hired. providing participants with a solid base for growth
Islam Salahuddin rather than a momentary amusement of directly
Those tools are indeed useful, but what good can picking low-hanging fruits.
a proficient handling of a screwdriver bring if one
does not know what it is and is not used for? Good Amid the distracting abundance of online
knowledge of statistics does not only provide a certificates, aspiring data professionals should
solid basis for correct analysis methods but also carefully consider their educational options and
ensures the ability for fundamental scientific prioritize the ones that provide a comprehensive
thinking and conceptual understanding. As The statistical education in addition to advanced tools
KPI Institute’s 2023 Global Trends Brief pointed and techniques. With proper education and the
out, the underlying critical mindset becomes even right skills, data professionals can become valuable
more crucial as AI generative tools become more assets to any organization, driving informed business
proficient (i.e. better and faster) at coding than decisions and improving overall performance.
top-notch data scientists. The field’s competitive
edge is currently shifting from tools to mindset.

Aspiring data analytics professionals are facing is essential for all the phases of data analysis, from
a dilemma. Along with the promising growth data acquisition to representation and reporting
of this field over the last few years, there has of results. Statistics also plays a critical role in the
been a corresponding rise in the number of data enrichment, exploration, analysis, and validation
analytics certifications available online, offered as of data. For instance, a solid understanding of
Massive Open Online Courses (MOOCs) by big statistics allows us to understand uncertainty in
companies and various platforms. However, many data, which enables us to carefully interpret and
of these courses focus on teaching advanced tools correctly communicate the results of the tested
and overlook the importance of building a strong hypotheses and predictions we make. Without this
statistical foundation. understanding, the results of analysis are commonly
interpreted and communicated with delusional
The origins of data analytics are debatable, but certainty that may lead to distorted business
only a few would deny its roots stretching deep into decisions.
the soil of statistics. The scope of data analytics
grew to include three elements: statistics, computer Overlooking statistics stems from the unrealistic
science, and business domain knowledge. While requirements in the job market. A systematic review
computer science is crucial in the field, it tends to of over 9,000 online job posts, published by the
be exaggerated at the expense of statistics, which Journal of Computer Information Systems, shows

52 53
 CAREER INSIGHTS CAREER INSIGHTS

Recommended Resources
Statistics

$41.5
Billion The likelihood of "intensive

23x
users" of customer analytics to
The estimated worth of The Global Data outperform their competitors in
Analytics Market in 2023 customer acquisition compared
Source: Global Data Analytics Market Size, Trends & Analysis - with "non-intensive users"
Forecasts to 2028" by Global Market Estimates Source: “DataMatics” survey by McKinsey Global Institute

24%
Proportion of businesses in the Asia Pacific identifying themselves as data-driven
Source: "The APAC Business Case for Democratizing Analytics Gets Stronger" by CDO Trends

54 55
 CAREER INSIGHTS CAREER INSIGHTS

Books Software

Microsoft Power BI
An end-to-end platform
with self-service analytics
at enterprise scale

Tableau
Talent Intelligence: Use Business Data and Analytics Strategy for Data-Driven Organization
Business: Unlock Data Assets Design: Delivering Perpetual Enhances customer
and People Data to Drive
and Increase Innovation with a Performance Gains Through the experience by providing
Organizational Performance
Results-Driven Data Strategy Organizational System real-time data
by Toby Culshaw (Amazon)
by Simon Asplen-Taylorby Toby by Rupert Morrison (Amazon)
Culshaw (Amazon)

Podcasts

Looker
Cutting-edge
business intelligence
and analytics tools

Data Skeptic Super Data Science DataFramed

hosted by Yajuan Si hosted by Jon Krohn hosted by Adel Nehme and
Richie Cotton

56 57
 CAREER INSIGHTS CAREER INSIGHTS

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Operationalizing Data Storytelling Where’s my data? Implications of

by The International Institute for cloud computing for you!
Analytics by Matthias Farwick

A Values-Led Approach to AI Ethics

in a Global Business
by The International Institute for Telling Stories with Data
Analytics by Daniel Posmik

Best Practices with Data Analytics Solving Global Grand Challenges

by The International Institute of with High Performance Data
Business Analysis (IIBA) Analytics
by David Bader

58 59
How Do You Stay Ahead of the Game? PERFORMANCE
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