1. Explain erp.
ANS-
ERP stands for Enterprise Resource Planning.
ERP systems are the kind of software tools that are used to manage the data of an enterprise.
ERP system helps different organizations deal with different departments of an enterprise.
It is the practice of consolidating an enterprise’s planning, manufacturing, sales, and marketing
efforts into one management system.
It combines all databases across different departments into a single database which can be easily
accessible to all employees of that enterprise.
Before ERP:
Figure – Before ERP
After ERP :
Figure – After ERP
Benefits of ERP:
• Increased efficiency and productivity
• Enhanced data accuracy and visibility
• Improved decision-making through real-time insights
• Reduced operational costs
• Improved customer service
2. Explain product lifecycle management with suitable example.
ANS-
The product life cycle is the journey a product or brand goes through from its creation to its
extinction.
It begins the moment a product launches, and ends when that product is finally taken off the
shelves for good.
1. Introduction
The first of the product life cycle stages is the introduction stage, where your product is first
introduced into the market. Most people won’t know about your product at this stage, so it’s a
struggle to make people aware of it and convince them of its benefits.
Example: The iPhone
Back in 2007, Steve Jobs and Apple released the first iPhone. At first, the product was met with
skepticism by many people — who needs a touchscreen?
2. Growth
The growth stage is where your business first finds success. At this stage, you’re getting a lot of
publicity, and you’re constantly gaining new customers and expanding your budget. In many
ways, it’s like the “honeymoon phase” of the product life cycle.
Example: Air fryers
The air fryer was first invented in 2010, but it wasn’t until 2015 that it exploded into popularity.
It then spent the next five years progressing through the growth stage.
3. Maturity
The most profitable of the product life cycle stages is the maturity stage. At this stage, your
business has become well-established in the market and is generating a steady flow of revenue.
However, competitors are now springing up left and right trying to sell the same product.
Example: Netflix
Netflix may have had humble beginnings, but by the mid-2010s, it had become the biggest
streaming platform in the world.
4. Decline
The final stage in our product life cycle overview is decline. Every business wants to avoid this
stage, because it’s where the demand for your products goes down and you stop stocking them.
At the bottom of this stage is extinction, which obviously isn’t desirable.
Example: Blockbuster
We already touched on Blockbuster earlier in this post as the biggest video rental chain of the
‘90s and early 2000s. If you wanted to watch a movie that was out of theaters, Blockbuster was
the place to go.
3. What is data mining? Explain OLAP with block diagram.
ANS- Data mining is the process of searching and analyzing a large batch of raw data in order
to identify patterns and extract useful information.
Companies use data mining software to learn more about their customers. It can help them to
develop more effective marketing strategies, increase sales, and decrease costs.
Data Mining Process for an E-commerce Company
Step 1: Understand the Business
Before looking at any data, the mining process starts by understanding what will define success
at the end of the process.
Step 2: Understand the Data
Once the business problem has been clearly defined, it's time to start thinking about data. This
includes what sources are available, how they will be secured and stored, how the information
will be gathered, and what the final outcome or analysis may look like
Step 3: Prepare the Data
Data is gathered, uploaded, extracted, or calculated. The data may also be checked for size as an
oversized collection of information may unnecessarily slow computations and analysis.
Step 4: Build the Model
With a clean data set in hand, it's time to crunch the numbers. Data scientists use the types of
data mining above to search for relationships, trends, associations, or sequential patterns.
Step 5: Evaluate the Results
After all the digging (data analysis), you've found some interesting patterns and insights. Now,
you need to explain what they mean in a clear way (interpretation) and present them to the
people in charge
Step 6: Implement Change and Monitor
Based on your findings, the leaders (management) will decide what to do next. Maybe the
information wasn't strong enough, or it wasn't quite what they were looking for. Or maybe it
revealed some big opportunities!
OLAP is a technology that enables users to interactively analyze multidimensional data from
multiple perspectives. It is used for complex calculations, trend analysis, and data modeling,
often in a business context to support decision-making.
Key Components of OLAP:
1. Data Sources: The raw data collected from various databases and systems.
2. ETL Process (Extract, Transform, Load): The process that extracts data from different
sources, transforms it into a suitable format, and loads it into a data warehouse.
3. Data Warehouse: A centralized repository that stores integrated data from multiple
sources.
4. OLAP Server: The engine that processes data in the data warehouse and supports OLAP
operations.
5. OLAP Cube: A multidimensional data structure that allows fast data retrieval and
analysis.
6. Client Tools: Interfaces used by end-users to query and analyze data, such as dashboards,
reporting tools, and data visualization tools.
OLAP Operations:
1. Slice: Selects a single dimension from the OLAP cube, providing a new sub-cube.
2. Dice: Selects multiple dimensions from the OLAP cube, creating a smaller cube.
3. Drill Down/Up: Navigates through levels of data, increasing or decreasing the level of
detail.
4. Roll-up: Aggregates data by climbing up a hierarchy.
5. Pivot (Rotate): Reorients the cube to provide an alternative presentation of data.
4. Explain business process re-engineering. Gives it advantages.
ANS-
Business Process Re-engineering (BPR) is a management strategy aimed at improving
organizational performance by re-designing and optimizing business processes.
It involves the analysis, design, and modification of pre-existing software systems.
The primary goal of this process is to enhance quality, performance, and maintainability of
system.
• Step 1 | Identify need for change
There is no logic of change, without a valid reason. This is most important to identify the need
for change, if any. It can be identified by looking into company’s performance matrices and
trend analysis. The need assessment should also factor benchmarking with competitors,
customer feedback, employee feedback etc.
• Step 2 | Finalize team of experts (internal / external)
Assemble a skilled and motivated team, including internal process experts and external process
engineering experts.
• Step 3 | Find the inefficient processes & measure current KPIs
Define and document current key performance indicators (KPIs) such as cycle time, changeover
time, inventory turnover, defect rate, and maintenance ratios.
Use business process mapping to detail processes and identify inefficiencies.
Resist the temptation to rush through the analysis and ensure thorough identification of problem
areas and setting of goals.
• Step 4 | Reengineer the processes and compare with improved KPIs
Implement proposed changes on a small scale, monitor KPIs, and evaluate the effectiveness.
Scale successful solutions across more processes, or revisit and revise solutions if they are not
effective.
Aim for substantial benefits and implement revised processes in spirit even if outcomes differ
slightly from the plan.
Example:
Consider a company struggling with slow order fulfillment. Here's a simplified BPR example:
1. Identify Need: High customer complaints about order delays.
2. Analyze: Map the order fulfillment process, identifying bottlenecks like manual data
entry or inefficient inventory management.
3. Reengineer: Implement an automated order processing system and improve inventory
tracking.
4. Implement & Monitor: Launch the new system on a small scale. If successful (faster
fulfillment times), roll it out company-wide.
Advantages:
• Improved understanding of business purpose and operations -
A successful BPR strategy gives companies a firm understanding of the present condition of
their business processes. This is important for businesses to streamline their operations and
prevent future mistakes.
• Simplified business processes -
Business Process Reengineering makes it easier to redirect the focus towards what’s essential.
With this, efforts are better aligned with company goals, and employees have a clear course to
follow.
• Higher efficiencies -
BPR helps to streamline processes, eliminate bottlenecks, and reduce waste, resulting in a more
efficient and productive organisation. This can reduce delays and errors significantly,
showcasing the benefits of reengineering processes.
• Improved customer service -
BPR can help identify and eliminate processes causing delays or dissatisfaction among
customers, resulting in better service and increased customer satisfaction.
• Enhanced flexibility -
BPR helps to make processes more adaptable and responsive to changing market conditions and
customer needs, which can be important for organisations that operate in a rapidly changing
environment.
• Cost savings-
By redesigning and optimising processes, BPR can help to reduce costs and improve the bottom
line.
• Better use of technology -
BPR can help to identify new ways to use technology to automate and improve processes,
which can lead to increased efficiency and cost savings.
5. Explain supply chain management.
ANS-
Supply chain management (SCM) is the centralized management of the flow of goods and
services to and from a company and includes all of the processes involved in transforming
raw materials and components into final products.
By managing the supply chain, companies can cut excess costs and deliver products to the
consumer faster and more efficiently.
Good supply chain management can help prevent expensive product recalls and lawsuits as
well as bad publicity.
The five most critical phases of SCM are planning, sourcing, production, distribution, and
returns.
A supply chain manager is tasked with controlling and reducing costs and avoiding supply
shortages.
5 Phases of Supply Chain Management
Planning
To get the best results from SCM, the process usually begins with planning to match supply
with customer and manufacturing demands. Companies must try to predict what their future
needs will be and act accordingly. This will take into account the raw materials or components
needed during each stage of manufacturing, equipment capacity and limitations, and staffing
needs.
Sourcing
Effective SCM processes rely very heavily on strong relationships with suppliers. Sourcing
entails working with vendors to supply the materials needed throughout the manufacturing
process.
Manufacturing
This is the heart of the supply chain management process, where the company uses its
machinery and labor to transform the raw materials or components it has received from its
suppliers into something new.
Delivery
Once products are made and sales are finalized, a company must get those products into the
hands of its customers.
This includes having a backup or diversified distribution methods. For example, how might a
company's delivery process be impacted by record snowfall in distribution center areas?
Returns
The supply chain management process concludes with support for the product and customer
returns. It's bad enough when a customer needs to return a product, but even worse if that's due
to an error on the company's part. This return process is often called reverse logistics.
Returns can also be a valuable form of feedback, helping the company to identify defective or
poorly designed products
Example:
6. Define data warehousing.
ANS- Data warehousing is the process of collecting, storing, and managing large volumes of
data from various sources to facilitate efficient querying and analysis.
