Development of KPIs for assessing the internal logistics of

UNIVEG’s Warehouse

Ana Patrícia Novo Trigo

Department of Engineering and Management, Instituto Superior Técnico, 2015

Abstract
In the current world, competition between companies in food industry is a frequent challenge. In
food industry’s supply chain, is known that customer’s demand is always changing and it is necessary
to change and readapt constantly the strategy of the companies. The companies’ logistic activity it’s a
critical point that allows this capability of each company to readapt more efficiently its competition.
Due to that, it is necessary analyze the UNIVEG Logistics Portugal’s warehouse and its
operation, because this is a company that works in food industry and cold chains, and it is necessary
to evaluate the performance of the different internal logistics’ areas inside the company. In this way, it
is intended to verify if the current key performance indicators (KPIs) that company applied are
appropriate to each area analyzed and if they are applicability. In the end of this paper, it should have
a development of new global performance indicators and suggestions to improve the oldest KPIs.
In the end, is developed three global indicators associated to the activities in the warehouse, like
the reception of goods, picking and shipping, through Swing Weighting method.
Finally is created a dashboard that will allow a quick view of the indicators associated to the
Operations Management.
Keywords: Warehouses, Key Performance Indicators, Internal Logistics, Supply Chains,
Perishable Products, Multicriteria Analysis, Swing Weighting, Dashboards
Logistics, and their operations are mainly focus
1. Introduction
on food products. The company is located at
At the present, logistics activity of the
the center of Portugal, in Riachos. Their focus
companies is a key factor for their
is to provide an excellent operational service,
development and ability to reach their
with quality and always focused on long
costumers faster and more efficiently than their
relationships between UNIVEG and costumers.
competitors. If they are more efficient, they will
UNIVEG is always concerned about their
have more costumers. It’s known that demand
clients, so it has been committed in the control
of the end costumer have a lot of uncertain,
of the internal logistics performance. This
and due to that, companies have to readapt
paper intends to focus on this constraint
quickly to changes in demand and reconfigure
identified by the company. In that way, the
their strategy (Beske, Land & Seuring, 2013).
present work will help the UNIVEG Logistics
UNIVEG is the second largest distributor of
Portugal to improve its measurement activities,
fruits at the business world. Their second
and therefore it will be proposed three global
biggest activity is the Transportation and

1
KPIs linked to their warehouse activity: changes in demand and reconfigure their
reception, picking and shipping of goods. It will strategy (Beske et al., 2013). This type of chain
be also created a dashboard that includes the have a lot of costs, with labor, maintenance
global indicators and the operational and electricity (Tassou et al., 2011)
management indicators. The workers in this type of industry should be
This present paper is divided in seven qualified and in constant training, because they
sections: Section 2 presents the literature need to use a lot of equipment in the
review; in Section 3 the problem that origins warehouse and in transportation. Also the
this paper; Section 4 the methodology applied interpretation of the temperatures’ sensors
in this work, the KPIs analysis and proposals; requires prevention and education of workers
in Section 5 the multicriteria analysis that (Stragas & Zeimpekis, 2014).
allowed to create the three global indicators is
2.2.1. Cold Supply Chains
presented; in Section 6 the dashboard created
There are different types of stores, like
is described and finally in Section 7 some
warehouses of perishable products and they
conclusions are taken.
can store food, fresh flowers, vaccines and
2. Literature Review other products that require refrigeration. Jol et
2.1. Key Performance Indicators (KPIs) al. (2006) consider perishable food like
KPIs are a set of measures which their focus products with a high risk of developing microbe
are the performance of critical processes or and they should be in an appropriate
activities that influences the success of the refrigeration storage conditions, controlled
company (Parmenter, 2007) and allow to carefully. These warehouses are very different
recognize which activities are more weak in from other types of warehouses, because the
terms of performance (Illies et al., 2009). products are typically stored for short periods
With KPIs, companies have more of time, and space is efficiently used due to the
consolidated information and the decisions are cooling that has a high cost (Bartholdi &
taken more easily (Meier et al., 2013). Hackman, 2005).
One of the challenges of these warehouses is
2.2. Food Supply Chains
avoiding contamination of the products,
A supply chain is considered an essential part
because they are very fragile and susceptible
of any business and it requires a concentration
to these situations. Another challenge is the
of companies’ resources for the chain works
inventory management due to the policies First
effectively and efficiently. This is important
In, First Out (FIFO) or First Expire, First Out
because the objective ist that the product
(FEFO) that must be applied depending on the
arrives faster to the final consumer (Kurien &
types of products (Bartholdi & Hackman,
Qureshi, 2011). In this global market with
2005).
constant changes, the ability to put the right
In addition, warehouses are not only a local
products at the right times and places, it’s as
storage of goods: have activities like reception,
important as achieving lower costs (Bogataj et
storage, picking and shipping of goods.
al., 2004). A supply chain is characterized as a
complex system, where suppliers, producers, 2.3. Swing Weighting Method
distributors and retailers work together to The multicriteria analysis is based on solving
satisfied the final consumer (Costantino et al., decision problems involving the evaluation of
2013). various options on multiple criteria. There are
In recent years, the concern about food weighting methods for determining which
supply chains has been increased. The food weights are associated with each criteria in
industry faces constant challenges due to the analysis.
increased complexity of operations involved in For swing weighting method is chosen one or
this industry (Aung & Chang, 2013). more decision makers, who will present their
Food chain stands out from the others because preferences regarding the criterias, with
is extremely dynamic and have a demand comparative processes. Through these
variability very strong. The demand of final weights, it’s possible to understand the
consume is uncertain and due to that, importance of each criteria for the decision
companies have to readapt quickly to the maker. The method starts its weighting

2
process putting all criteria in a worst scenario, The actual KPIs implemented on UNIVEG
creating a baseline as worst case scenario. Logistics Portugal are a very large list and
Thus, the decision maker is asked to choose don’t focus on the essencial aspects that
which criteria has more relevance to change company wants to measure. So, the main
the worst scenario to the best scenario, and problem that company faces is that actual KPIs
that criteria will have 100 points, and then it’s don’t suffer a lot of changes since they were
eliminated from the choices. Consecutively, the created, so it’s necessary a big revision of that
decision maker is requested to choose again list, and analyse all the aspects related to that
another criteria that represents great KPIs, like objectives, the way that they were
importance to change the worst scenario for formulated and analyse its historic. Another
the better, comparative to the first criteria aspect are the fact that company needs KPIs
choosen, having this second a value less than that allow lower costs, so it’s necessary to
100 points, which is determined by the create indicators that allow the company to
decision maker. This second criteria is understand which activities can reduce costs.
removed from the process and so on. At the
4. Methodology
end, it is obtained in descending order of
To do this work, the methodology implemented
relevance the set of criteria selected by the
was the following:
decision maker. To complete the process, it is
i. Initially, it was requested historical data of
necessary to determine the weights of the
the company of all the KPIs already
criteria that will have to belong to a range
implemented. It has been only possible to
where total of the sum is the unit (Goodwin &
collect data for four consecutive years since
Wright, 2004).
2011, was the year that KPIs were
3. Case Study implemented;
UNIVEG Logistics Portugal started their ii. The annual objectives of each KPI were
activity in Riachos at 1999. It’s a worldwide also asked, analyzing each of them and if
supply chain, which starts a the suppliers, the goals have been achieved annually;
being the current company responsible to do iii. Through the data collected, graphs for each
the transportation service and store the indicator were generated, that allowed to
products at the warehouse in Riachos. Then, understand what is the trend over time and
they shipped in their truck fleet to the final the feasibility of them;
costumers. iv. After this analysis, it has been suggested
The most important client is Makro, the larger some changes in KPIs already
wholesaler that company has as a client. In implemented, as well the creation of new
their products performs the crossdocking, ones that prove to be useful in the future for
which is a good advantage for UNIVEG. The the company;
company make all the transport of Makro
4.1. Classification of KPIs implemented
requests to their stores all over the country.
UNIVEG implemented several KPIs. The next
UNIVEG works with other companies like Lidl,
list presents all the indicators analysed on this
Intermarché and other companies with
work:
smallest dimension.
- Evaluation of Suppliers;
UNIVEG Logistics Portugal have, actually,
- Number of Picking Boxes;
three services for their costumers:
- Number of In Pallets;
Tranportation, Ad-Value Services and
- Number of Stock Pallets;
Logistics’ Storage Services.
2 - Number of Out Pallets;
With 17.000m warehouse at Riachos,
- Number of CrossDocking Pallets;
UNIVEG can storage 14.000 pallets, in multi-
- Productivity of Fresh Picking;
temperature environment.
- Productivity of Frozen Picking;
Their three fundamental activities at
- Productivity of Reception;
warehouse are reception, picking (Picking-by-
- Compliance with Daily Deliveries in Stores;
Line or Picking-by-Store) and shipping, which
- Clients & UNIVEG Breaks;
will be the focus of this paper, at Section 5.
- Volume of Extra Hours;
- Costs of Extra Hours;

3
- Level of Absenteeism;  Most of the indicators implemented on
- Compliance with Training Plan; UNIVEG are classified as internal processes.
- Number of Work Accidents; However, according to the literature review, it
- Service Level; can be classified through more than one
- Compliance with Maintenance Actions; perspective, like indicators associated with
- Number of Failures face of Shipped Pallets; continuous improvement, which are presented
- Number of Projects Developed; in the category of Transversals, as Number of
- Number of Interventions Performed; Non-Conformities at Warehouse, Number of
- Reduction of Energy Consumption; Customer Complaints at warehouse and
- Number of Non-Conformities at Warehouse; Effectiveness of Picking Control which can be
- Number of Customer Complaints; encompassed (in addiction to Internal
- Effectiveness of Picking Control. Processes), as well as from the perspective of
It is possible to understand that there are two innovation / learning since they are used to
groups of indicators: strategic indicators and improve the company's service and to innovate
operational indicators. In this way, strategic all their business.
indicators are all the indicators associated with 4.2. KPIs Analysis
the financial perspective (Clients & UNIVEG In this work all KPIs were analysed, but in
Breaks, Costs of Extra Hours and Reduction of this paper it will only be presented the most
Energy Consumption). These indicators help relevant KPIs which should be deeply
the company to understand its operation analysed.
regarding costs while trying to minimize costs
- Number of Interventions Performed
by optimizing its performance. On the other
This indicator refers to interventions
hand, the group of operational indicators (all
performed with workers’ requests. This
other that is related to the non-financial
indicator differs from the Maintenance Actions
indicators) are the ones are used to control
because the maintenance indicator reffers to
activities or company’s operations.
preventive actions and these are corrective
The classification used for these indicators
actions. These actions may occur in
was based on SCOR model that presents six
company's facilities, not necessarily just inside
phases, such as Planning, Supply, Production,
the warehouse but it might also include
Distribution, Return and Transversals
maintenance work in the offices, bar, among
(Rodrigues et al., 2006). Other perspectives
others.
have been attached, with Balanced ScoreCard.
Historical data have values that exceed the
This perspectives are based on financial
100% compliance in several months of 2013
perspective, clients, innovation and internal
and 2014. This means that there were more
processes (Kaplan, 2010).
interventions performed than requested in the
With these models, it was possible to
beginning of the month. Peaks are
understand that most of the indicators
concentrated in the months of more work,
implemented have their focus on the
during the summer period, when the work is
production phase. It is considered the most
intense and more damages occur, requiring
important activity, and the focus of concern by
maintenance interventions. Since the objective
the company;
of complying with this indicator is the 85%
 The financial indicators classified in this
threshold or higher, it is suggested that the
perspective have been well classified and
goal is increased to a value close to 100%.
according to current literature, like Costs with
Implementing TPM (Total Productive
Extra Hours, Reduction of Energy
Maintenance) makes workers more versatile,
Consumption and Clients & UNIVEG Breaks
there is no need to wait for the maintenance
(with the products of their clients);
team to solve certain situations in which
 The indicators classified as Transversals are
resolution is simple.
presented as embodied indicators across all
the supply chain, such as Maintenance - Number of Work Accidents
Actions, Projects Developed, Clients’ This indicator presents a high volatility every
Complaints; quarter. Achieving only one accident per
quarter is a goal not reached in most of the

4
registers. To improve this indicator, it is satisfactory situation for the company would be
proposed the following suggestions: to achieve 20% more than expected, which
• Check if the current training given to workers means, to reach 165%.
at safety level is appropriate; For the other mentioned indicators, they were
• Meetings, set and spread safety standards; reformulated in the same way, presented in
• Check if the working conditions in the next equations (2), (3), (4) and (5):
𝑃𝐼
warehouse are favorable to workers; 𝑃𝑎𝑙𝑙𝑒𝑡𝑠 𝐼𝑛 = 𝑛 ∗ 100 (2)
𝑃𝐼 𝑛−1
• Kaizen improvement: this philosophy implies 𝑃𝑆𝑛
𝑃𝑎𝑙𝑙𝑒𝑡𝑠 𝑆𝑡𝑜𝑐𝑘 =
𝑃𝑆𝑛−1
∗ 100 (3)
the practice of activities that continuously
𝑃𝑂𝑛
improve all functions, and involve all 𝑃𝑎𝑙𝑙𝑒𝑡𝑠 𝑂𝑢𝑡 =
𝑃𝑂𝑛−1
∗ 100 (4)
employees. Thus, it is possible to improve the 𝑃𝑎𝑙𝑙𝑒𝑡𝑠 𝐶𝑟𝑜𝑠𝑠𝐷𝑜𝑐𝑘𝑖𝑛𝑔 =
𝑃𝐶𝐷𝑛
∗ 100 (5)
𝑃𝐶𝐷𝑛−1
activities and processes to eliminate the
Where:
"waste", which is, the work poorly performed.
𝑃𝐼𝑛 , 𝑃𝑆𝑛 , 𝑃𝑂𝑛 , 𝑃𝐶𝐷𝑛 represents the month under
- Operations Management consideration reflected in the number of pallets
When the indicators related to the Operations in the current year n;
Management area were analysed, some 𝑃𝐼𝑛−1 , 𝑃𝑆𝑛−1 , 𝑃𝑂𝑛−1 , 𝑃𝐶𝐷𝑛−1 represents the month
problems with the way that indicators were under consideration reflected in the number of
defined emerged. The indicators Number of pallets in the previous year.
Picking Boxes, Number of In Pallets, Number The goals for each indicator have been
of Stock Pallets, Number of Out Pallets and defined with the same logic as the goal for
Number of CrossDocking Pallets, were all Picking Boxes indicator and the results are
evaluated on a monthly basis, but only reflect present in Table 1.
the number of boxes or number of pallets Table 1 – Goals for new indicators
corresponding to the situation which they KPI Goal Best Situation
describe. Although the literature on KPIs Pallets In 145% 185%
allows indicators being defined with absolute Pallets Stock 130% <130%
values, the company perspective on these Pallets Out 152% 172%
indicators relates to a strategic level, and thus Pallets
the information that UNIVEG wants to absorve CrossDocking 140% 160%
of these KPIs, indicates that they are defined in
5. Global indicators
a wrong way. Due to this, new ways to
Since the Reception, the Picking and
evaluate these indicators have been suggested
Shipping are the core activities of a perishable
in a way to keep their real importantance. The
products’ warehouse, it became necessary to
suggested is registered in the following
establish a way to measure the performance of
equation (1):
𝐶𝑝𝑛 these activities, on a monthly basis. The
𝑃𝑖𝑐𝑘𝑖𝑛𝑔 𝐵𝑜𝑥𝑒𝑠 = ∗ 100 (1)
𝐶𝑝𝑛−1 purpose of its creation is to provide to UNIVEG
Where: a tool that allows them to quickly understand if
𝐶𝑝𝑛 represents the month under consideration these activities are carried out in accordance
reflected in the number of cases in the current with its objectives.
year n; In order to develop these indicators, it was
𝐶𝑝𝑛−1 represents the month under necessary to choose two decision makers from
consideration reflected in the number of cases the company. For the creation of global
in the previous year. indicators, it was used the multi-criteria
To define its goal, current data was analysis since their creation involve multiple
considered. Thus, the current 2015 objectives criteria. The methodology used was the
have been compared the corresponding 2014 following:
ones. Applying Equation (1), it was found that i. Function value: the creation of this function
the average for the year 2015 is 145%. This can transform value in performance,
means that in addition to performing the same through bisection method. This technique is
number of Picking Boxes of the previous year introduced as a way to identify the most
(it means 100%), the company wants to preferred and least preferred scenarios,
overcome these values by 45%. The most

5
 and an intermediate point that is equidistant Value KPI5 KPI6 KPI7 KPI8
between the borders; (Points) (Boxes) (%) (%) (Pallets)
ii. Weighting Methodology: with Swing 100 190 30 172 32
Weighting method, it is possible to obtain 75 180 25 164 29
weights for each of the attributes involved; 50 155 20 152 24
iii. Additive Aggregation Model: through this 0 130 15 100 18
model it will be obtained a final formulation
for the desired indicators; 5.2. Swing Weighting Method
iv. Sensitivity Analysis: This will evaluate the This method has three steps:
sensitivity of each indicator compared to the  Ordering criteria by their importance for
variations of the obtained weighting decision maker;
coefficients.  Quantification of weighting coefficients;
5.1. Value Functions  Coefficients’ normalization, so the total sum
For the creation of this global indicator, the is unit.
currently used KPIs related to this activity were  Ordering Criteria
selected. For Reception Global Indicator: it was
For Reception Global Indicator it was used: questioned to decision makers which of the
 KPI1 = Pallets In; criteria (points of view) the "swing" from the
 KPI2 = Reception Productivity. worst to the best scenario would result in the
For Picking Global Indicator was used: greatest improvement in overall attractiveness,
 KPI3 = Picking Boxes; representing in what criteria the improvement
 KPI4 = Fresh Picking Productivity; is more significant for them. The answer was
 KPI5 = Frozen Picking Productivity; KPI1, so it means that the weight of this
 KPI6 = Effectiveness of Picking Control. indicator (𝑝1 ) is higher than the weight of KPI2,
For Shipping Global Indicator it was used: 𝑝2 . It means that 𝑝1 > 𝑝2 .
 KPI7 = Pallets Out; For Picking Global Indicator the result was
 KPI8 = Shipping Productivity. 𝑝4 > 𝑝5 > 𝑝3 > 𝑝6 and for Shipping Global
The Bisection Method was used where Indicator the result was 𝑝7 > 𝑝8 .
decision makers have identified what is the  Quantification of Weighting Coefficients
best and worst case scenario in KPIs in In this step, it was asked to decision makers
analysis, as well as an intermediate point that for Reception Global Indicator:
is equidistant to the extreme scenarios. This “How much you classified the change from the
method is presented as a simple way of turning worst in KPI2, for the same change in the worst
performance of the KPIs in a range equal case scenario to the best scenario KPI1?”
Decision makers answer if that change
between of them, in order to be used in the
happens in KPI2, it will have a value of 40
final indicator. This value function becomes
compared to KPI1. So, it was possible to obtain
valuable because it would not include 40
indicators with different measures. Decision the weight of 𝑝2 non-normalized, 𝑝2 = ( )𝑝1 .
100
makers decide the values for the best and For Picking Global Indicator:
worst level scenarios, between 100 points and “How much you classified the change from the
0 points, for each of the represented indicators. worst in KPI3, KPI5, KPI6, for the same change
The intermediate point has 50 points, in the worst case scenario to the best scenario
KPI4?”
representing the neutral scenario.
Through their answers, it was obtained
The decisions made by decision makers are 70 58 20
represented at Table 2. 𝑝3 = ( ) 𝑃4 ; 𝑝5 = ( ) 𝑃4 ; 𝑝6 = ( ) 𝑃4 ;
100 100 100
Tabela 2 – Values of each indicator in analysis For Shipping Global Indicator:
Value KPI1 KPI2 KPI3 KPI4 “How do you classified the change from the
(Points) (%) (Pallets) (%) (Boxes) worst in KPI8, for the same change in the worst
100 185 40 165 200 case scenario to the best scenario KPI7?”
60
75 170 35 155 190 The answer revealed that 𝑝8 = ( )𝑃7 .
100
50 145 30 145 180
0 100 10 100 175

6
  Coefficients’ Normalization
In this final step, it was necessary to 59

Global Performance
Worst
normalize the coefficients, in a way that their
54 Scenario
total sum be 1. So, through the equation (6):
𝑝 Neutral
𝑃𝑖 = ∑𝑛 𝑖 , ∀ 𝑖 = 1,2, … , 𝑛 (6) 49
𝑖=1 𝑝𝑖 Scenario
100 44
Finally, it was obtained that: 𝑃1 = = 0.71;
140 Best
40 70 100 39
𝑃2 = = 0.29, 𝑃3 = = 0.28, 𝑃4 = = Scenario
140 248 248
58 20 0 0,2 0,4 0,6 0,8 1
0.40, 𝑃5 = = 0.24, 𝑃6 = = 0.08, 𝑃7 = Weight variation of KPI1
248 248
100 60
= 0.62 and 𝑃8 = = 0.38. Figure 1 – Weight variation of KPI1
160 160
Through weight variation of KPI1, it’s possible
5.3. Additive Aggregation Model see that by increasing the value of 𝑃1 , value of
The Additive Aggregation Model allows the 𝑃2 decreases, progressing to the worst for a
desired global indicator, in which it was better case scenario. If the range of values
possible to apply all the results obtained in between criteria weights is bigger, global
previous steps. The equation (7) represents performance tends to assume the values
this model and it will be applied to obtain the associated with the criteria with the highest
three final global equations desired. weight. On the order hand, if the interval
𝑉(𝐺𝐼) = ∑𝑛𝑖=1 𝑃𝑖 𝑣𝑖 (𝐺𝐼) (7) between the weights of the two criteria is
Where: minimal, the overall performance tends to
 𝑉(𝐺𝐼) represents the value of the desired intermediate values between the criteria
global indicator (GI); values. This happens because the weights are
 𝑣𝑖 (𝐼𝐺) represents the parcial value of GI of negligible, meaning that they are similar and
point of view i therefore they do not affect the end value
where 𝑣𝑖 (besti) = 100 e 𝑣𝑖 (worsti) = 0; performance in a large scale. It is also
 𝑃𝑖 represents the weighting coefficients of important to note that these weighting values
point of view i only influence clearly Global Performance if the
where ∑𝑛𝑖=1 𝑃𝑖 = 1 and 𝑃𝑖 > 0 ( i=1,2,…,n). input values 𝑣1 and 𝑣2 are more dissimilar,
Through equation (7), it was possible to obtain which in this scenario is not what happens,
the three global indicators desired: since the values used are similar.
 Reception Global Indicator  Picking Global Indicator
𝑉(𝑅𝐺𝐼) = 0.71 ∗ 𝑣1 + 0.29 For this analysis, input values are:𝑣3 = 60, 𝑣4 =
𝑉(𝑃𝐺𝐼) = 0.28 ∗ 𝑣3 + 0.40 ∗ 𝑣4 + 0.24 ∗ 𝑣5 + 0.08 ∗ 𝑣6
64.5, 𝑣5 = 60 and 𝑣6 = 81. Again, these values
 Shipping Global Indicator
were get by random values, because the
𝑉(𝑆𝐺𝐼) = 0.62 ∗ 𝑣7 + 0.38 ∗ 𝑣8
confidentiality agreement. Sensitivity analysis
5.4. Sensitivity Analysis was represented in Figure 2.
In all of the next sensitivity analysis, it was Worst KPI3,
considered three scenarios for each KPI: 70 KPI5
Worst KPI4
- Worst Scenario, where weight of KPI in 69
Global Performance

analysis is lower than other KPIs; 68 Worst KPI6

- Neutral Scenario, where KPIs’ weights 67
- Best Scenario, where weight of KPI in Neutral KPI3,
66 KPI4, KPI5, KPI6
analysis is higher than other KPIs.
65 Best KPI3, KPI5
 Reception Global Indicator 64
To run this analysis, it was used as input 𝑣1 = Best KPI4
63
60 and 𝑣2 = 40. These values are random, Best KPI6
0,1 0,25 0,4
derivated from confidentiality agreement. The
Weight variation of KPI3
values was obtained from the tranformation by
Figure 2 - Weight variations of all KPIs
value function created at Section 4.1. The
Since the values of 𝑣3 = 𝑣5 = 60, they were
sensitivity analysis is presented in Figure 1.
grouped, as it can be seen in the Figure 2

7
subtitle, in line of Best and Worst scenarios of i. Data collection of Operations Management
both KPI3 and KPI5. It is possible to verify by indicators, like Picking Boxes, Pallets In,
the graph that in the column of the weight 0.1 Pallets Stock, Pallets Out, Pallets
all bad scenarios of four indicators are shown. CrossDocking, Productivity of Fresh Picking,
In the column of the the weight 0.25 only one Productivity of Frozen Picking and Productivity
point is showed, which is related to all neutral of Reception;
scenarios (as having the same weight, its ii. Conversion of real data of the indicators
performance is equal). Finally, in the column of throught value scales defined in Section 4.1,
the weight 0.4, it is demonstrated the best so they can be used in the Global Indicators
scenarios for each indicator. It is possible to created;
note that the KPI6 influences more the result of iii. Creation of dashboard design, based on the
overall performance, because of the higher of colors of the company;
input values. If it has a weight lower or higher iv. Creation of five pages on dashboard, titled
compared to others, this would influence with Reception Global Indicator (“IGR”),
negatively or positively more than the other Picking Global Indicator (“IGP”), Shipping
indicators. In conclusion, KPI6 is more robust, Global Indicator (“IGE”), “KPIs Paletes_Caixas”
dominating the final overall performance of the and “KPIs Produtividades”;
picking activity. v. Each page needs to match the indicators
whose name describes.
 Shipping Global Indicator
In this analysis, it was used as input 𝑣7 = 52 6.1. Visual Dashboard
and 𝑣8 = 65. Again, these values are random Each page of this visual tool is an indicator or
and result from confidentiality with company. a set of indicators important for the company,
and due to that, they deserve more attention
66
Worst than the remaining indicators implemented on
Global Performance

63
Scenario UNIVEG Logistics Portugal. This set of
60
Neutral indicators reflects the logistics company, more
57
Scenario specifically, the entire operations management
54 of their warehouse. Thus, it is important to
51 Best
monitor all these data in order to understand if
0 0,2 0,4 0,6 0,8 1 Scenario
the objectives are being achieved or not, on a
Weight variation of KPI7 monthly and annual basis.
Figure 3 - Weight variation of KPI7 Each page of the Global Indicators includes
Again, through Figure 3, can be conclude
two types of information:
that the variation of 𝑃7 influences proportionally
 On the left side of the page it is possible to
the variation of 𝑃8 . In this situation, as the input
find all the information relative to global
of 𝑣7 is higher than 𝑣8 and this analysis
indicators in analysis, with one table to fill with
focuses on the variation of the 𝑃7 , then the
current values and automatically, the
performance tends to become worse dashboard converts that into values within the
depending on the positive variation of that defined value function through interpolations
weight. If the determined weights were more created, like it is possible to see in Figure 4.
diverse, it would be advisable to reassess the
importance of KPI7 relative to KPI8. Since the
current weights are similar, it is not necessity
to do that review.
6. Dashboard
This dashboard was created to facilitate the
results’ view of KPIs included on Operations
Management of the company. The dashboard Figure 4 - Tool to determine the Global Performance
To obtain the desired value of overall
was created on Excel program, aiming to
performance, it is assigned a "speedometer"
facilitate its use by UNIVEG workers.
that automatically varies with the value
The methodology applied was:
obtained in global performance calculated,

8
which indicates if this is within the desired
range (between the neutral and optimal values,
designated "Melhor" area) or if that is not in the
desired range (between the worst and neutral
scenario, called "Pior" area).
 On the right side of the page it’s possible to
find a tool that is illustrated in Figure 5, where
all Global Performances of every month in
2014 were determined. As this indicator did not
exist before this work, it was necessary to Figure 7 – Chart to compare same month in diferent years
calculate all Global Performance values to be Thus, it is the goal of this dashboard to
able to check their trend. With this new become useful, a quick view and easy
information, it is possible to see what was the understanding for the company, if they need to
trend on last year of each global indicator. change or not the methodologies applied in the
activity under review by the company.
7. Conclusions
In this paper there were developed tools that
will help UNIVEG Logistics Portugal in their
control of activities that are their core business.
All indicators used in the company were
analysed in a way to improve their results and
suggesting what can be modified.
New ways to measure operational
Figure 5 – Tool to see the evolution of Global Indicators
management area were created with the goal
In the other hand, each page of KPIs
of transforming their operational indicators in
Caixas_Picking or KPIs_Produtividades has
strategic, since that is their view of them.
two types of information:
Finally, global indicators for the most
 On the left side, a table that it is possible to important activities related to UNIVEG’s
select the year to see all the values obtained in warehouse have been created. These global
each month of this year, and returns those indicators related to reception, picking and
results in a graph, presented on Figure 6. shipping of goods will help company to
understand if their efforts have been used
correctly and if it needs to change something
to performed better.
In the end of this work, it has been developed
a dashboard that reveals as a visual tool and
useful, allowing UNIVEG to undestand if they
are matching their goals.
In the future, to contribute for this work, it can
Figure 6 – Table of the trend each year be developed a complete dashboard that links
 On the right side, a chart that allows the all the database of the company to the all
user to perform a comparison between the database of the dashboard.
same month values across different years, as it
8. References
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month under review.

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