Project Organizational Responsibility Model - ORM

DPR Projects - Jan/2015 to Dec/2018
Implementation of the Organizational
Responsibility Model - ORM at Prodemge
Directorate of Infrastructure and Production - DPR
2015 - 2018
November/2018

1. INTRODUCTION 3
2. CONTEXT AND OBJECTIVE OF THE PROJECT 3
3. SCOPE OF THE PROJECT 4
4. DIAGNOSIS, PREMISES, REQUIREMENTS AND RISK OF THE PROJECT 5
5. GENERAL PROJECT STRATEGY 8
6. PARTICIPANTS AND INTERNAL AREAS INVOLVED 8
7. PARTICIPANTS AND EXTERNAL AREAS INVOLVED 8
8. ESTABLISHMENT OF AGREEMENTS AND OTHER LEGAL INSTRUMENTS 8
9. TECHNICAL DESCRIPTION OF THE SOLUTION 8
10. SOLUTION ARCHITECTURE 10
11. GENERAL DEPLOYMENT PLAN 12
12. PROJECT DEADLINE 12
13. PROJECT COST 12
14. PROJECT IMPLEMENTATION PHASES 12
15. OTHER PLANNED ACTIVITIES 24
16. CONCLUSION AND FINAL CONSIDERATIONS 24
17. TECHNICAL TEAM 30
18. REFERENCES 30

INTRODUCTION
Brazil is looking for a new development model, a model that will expand opportunities to learn, work
and produce the driving force of economic growth, as indicated by Johannpeter and Unger in 2009 [1].
The construction of this model depends on institutional innovations in several sectors of public
policies, such as the applicability of complex system models with positive results in the strategic
planning of organizations. The Organizational Responsibility Model - ORM [2] is presented as one of
these initiatives with an emphasis on problems related to management by results.
CONTEXT AND OBJECTIVE OF THE PROJECT
The objective of this project is to prepare Prodemge to face the challenges of Digital Transformation,
through the implementation of certain stages of the Organizational Responsibility Model (ORM), with
an emphasis on the improvement of the public services provided in light of a demand for services that
is higher than the installed capacity.
Figure 1 - Organizational Responsibility Model - ORM
1. Qualification of the Demand - This is a database with information about all the Information and
Communication Technology (ICT) services, presented in the format of a Service Booklet. The
identification of demand is carried out according to three criteria: size, complexity and priority;
2. Capacity Plan - Survey of the amount of personnel required to perform the activities that
comprise the services described in the Services and Business Management and Support Booklets,
adapted from the TDABC model (Kaplan and Anderson, 2004) [3];

3. Operational Level Agreements (OLAs) - OLAs seek to ensure the quality of the services
delivered to customers. These are agreements established between a principal executing area
(responsible for executing a particular service for the customer), and a Secondary area, whose
responsibility is to provide the service internally and to monitor the fulfillment of the goals of both
parties;
4. Productivity Optimization - Establishes a relationship between the demand for services and
the productivity of people in the execution of the activities. The demand may be distributed according
to queuing theory (Andrade, 2002) [4] or intelligently. In this case, the complexity and priority criteria
are used for their qualification, in order to establish the best cost/benefit ratio;
5. Employee Evolution - A model that addresses the employee's life cycle in the company with a
structure similar to the model of Aging Chains proposed by John Sterman (2000) [5];
6. Employee Experience - A model that facilitates the dissemination of knowledge so that the
employee can deal with the complexity of the demands.
7. OLA Loops between Areas - Mapping of interdependence between areas, through which it can
be observed that a certain area A depends on area B to perform its service and vice versa, thereby
establishing a loop between areas.
8. Organizational Responsibility - Union of the mapping of the loops of the areas with the
adaptation of the PageRank model [6], which uses the same search algorithm as Google. This relates
to the elaboration of a ranking of the most accessed pages in a network on the internet. It also takes
into account the access of the origin pages, raising the quotation of the address accessed.
In the ORM the reasoning is analogous. However, the ranking demonstrates the bottleneck in the
execution of the activities that make up the service. The model distributes responsibility for the
execution of services to all areas of the company involved in the process.
SCOPE OF THE PROJECT
The scope of the project is related to the implementation of the ORM stages, directly linked to the
Business vision of the Corporate Architecture Framework for Interoperability in Support of Governance
- FACIN [7], to prepare leaders and organizations for the future [8].
The FACIN is a benchmark for governance support, providing interoperable electronic services and
facilitating simplification, speed and effectiveness between governments, and between governments
and citizens, organizations and companies. It is based on the use of current and innovative best
practices, based on the concept of corporate architecture, in order to reinforce the consistent view of
each government organization as an integrated system.

Figure 2 - Corporate Architecture Framework for Interoperability in Support of Governance - FACIN
DIAGNOSIS, PREMISES, REQUIREMENTS AND RISK OF THE PROJECT
The project's premise is the implementation of certain stages of the ORM, adding subjective (Master
CIO [9] and Competencies [10]) and analytical (ORM [11]) components, incorporating the use of
Machine Learning to help lead the transformations of organizations from the traditional to the
Exponential [12].
Figure 3 - Exponential Organization Tripod
Alvaro Mello from Gartner believes that digital business is increasing the complexity of the CIO role. It
is necessary to develop personnel and change cultural issues for the organization to succeed.
Master
CIO
Organizational
Responsibility
Model - ORM
CompetenciesDevelop the
Competencies Your
Workforce Needs for
the Digital Ecosystem
Gartner
Are you a CIO master?
Gartner
Exponential Organization Tripod
Use of Machine Learning
helping to lead the
transformations of public
organizations from traditional
to Exponential
Be Exponential
Singularity University
https://su.org/enterprise https://goo.gl/kGcjfe
https://goo.gl/oY46Kc
https://lnkd.in/dqY9mds

Becoming a Master CIO is not about a determined set of skills or knowledge of a technology, but is
about adopting and promoting the following ten characteristics:
Figure 4 - Ten characteristics of the Master CIO
CIOs also have a responsibility to ensure that the workforce can operate in a digital ecosystem,
according to Lily Mok of Gartner. CIOs need to identify and develop the following competencies in the
workforce:
Competency Description
Adaptability Demonstrates flexibility, agility and the ability to respond effectively to changing environments,
expected and unexpected, while working with individuals, groups and team members. Being open to
new challenges. Changes own ideas or perceptions in response to changing circumstances.
Improvises, alters standard procedures when necessary, and multitasks as required.
Business Acumen Demonstrates awareness of internal and external dynamics, and an acute perception of the dimensions
of business issues. Conducts research and identifies, collects and analyzes information about the
markets, economies, political environment, technology trends and business operation issues to make
informed decisions. Develops approaches and solutions that are clearly linked to the organization's
strategy and goals for optimal performance.
Collaboration/Synergy Collaborates with other members of formal and informal teams in the pursuit of common missions,
vision, values and goals. Places team needs and priorities above personal needs and priorities. Fosters
synergy within and across teams, building on mutual trust and respect. Involves others in making
decisions that affect them. Draws on the strengths of colleagues and fellow team members, and gives
credit to the contributions and achievements of others.
Decisiveness Assesses the scope and potential impact of an issue or opportunity. Uses business criteria and values
to evaluate alternative courses of action. Makes a timely choice based on the options and information
available.
Design Thinking Possesses the ability to take an analytic, creative and iterative process that leads to desired outcomes
that benefit the end user (the customer). Able to search for information, and depict ideas and creative
processes visually and verbally. Demonstrates the ability to flexibly use different problem-solving
strategies and select the one that best meets the requirements of the situation. Evaluates
different/multiple solutions to a problem, creates and prototypes models. Communicates and works with
others across disciplines, gathers feedback on different solutions, and redesigns until the best possible
solution is determined. Searches competing alternatives before moving to decision making. Keeps the
big picture of the problem in mind while focusing on its specifics.
Digital Dexterity Demonstrates fluency in cognitive ability and social practice needed to leverage and manipulate media,
information and technology for advantage in unique and highly innovative ways. This includes the ability
to participate across virtual and physical environments to communicate, collaborate and mobilize social
and other networks in agile and creative ways for better personal and business outcomes.
Diversity Mindset Maintains an awareness and openness to diversity as defined in a multitude of way to include
demographics, cultures and markets. Has the inclination and capabilities to integrate across diversity.
Accommodates the differences presented and conveys respect for different perspectives. Listens with
an open mind to fully understand and adapt behavior to accommodate others. Fosters inclusion and
sharedness.
Growth Mindset Takes ownership of personal growth. Embraces the concept that intelligence and talent can be
developed through continuous learning. Acquires strategies for gaining new knowledge, behaviors and
skills. Engages in learning from others, both within and outside the organization. Tries new approaches
and broadens the scope of work to learn from work assignments. Sees challenges as opportunities to

Competency Description
grow and learn, and is resilient, even when faced with failure.
Innovative Improves organizational performance through the application of original thinking to existing and
emerging business models, methods, processes, products and services. Employs sound judgment in
determining how innovation, radical or incremental, will be deployed to create business value.
Outcome-Driven Focuses on desired results and business outcomes. Sets and achieves challenging goals. Clearly
defines mutual expectations of self and others in a team setting. Takes appropriate actions to ensure
obligations are met. Defines performance standards in terms of doing what is appropriate and doing it
well. Revises standards in response to changing business needs. Is resourceful and takes calculated
risks to achieve results; works to achieve goals despite barriers or difficulties.
Political Savviness Demonstrates an understanding of organizational and political reality. Is aware of how the organization
is structured, its culture, and different power groupings and agendas. Uses this understanding to inform
and shape behaviors and decisions and act accordingly. Effectively negotiates and builds coalitions
internally and externally to achieve missions and objectives. Possesses skills in empathy, conflict
management and option generation based on risk-reward calculations.
Risk Taking Handles changes and uncertainties with ease and with the ability to move forward quickly. Identifies
and acts upon opportunities for continuous improvement. Demonstrates a willingness to make high-risk
decisions when necessary and with prudent judgment. Is able to act with minimal planning and to take
actions in which the benefits to efficiency and effectiveness are weighed against potential risks.
Figure 5 - Critical Workforce Competencies for Building Digital Business Capabilities
Source: Gartner (November 2017)
Machine Learning is a method of data analysis that automates the construction of analytical models. It
is a branch of artificial intelligence based on the idea that systems can learn from data, identify
patterns and make decisions with the minimal human intervention.
Machine Learning can be implemented by Scikit-learn, a free software library using Python
programming language, according to Stefan Kojouharov.
There are a number of classification, regression and clustering algorithms including support vectors,
random forests, gradient enhancement, k-means and DBSCAN, designed to interoperate with
numerical and scientific Python libraries (NumPy and SciPy).
Figure 6 - Twelve competencies of the workforce

GENERAL PROJECT STRATEGY
The project strategy is to transpose the ORM simulation data [13] into the actual data of the Company
and insert it into the Machine Learning system in order to predict which activities should be performed
in traditional (Modal 1) or Exponential (Modal 2) Bimodal IT.
Figure 7 – Simulation of the ORM
PARTICIPANTS AND INTERNAL AREAS INVOLVED
Members of all areas related to the Infrastructure and Infrastructure and Production Directorate of
Prodemge participated in the Project.
PARTICIPANTS AND EXTERNAL AREAS INVOLVED
Gartner Analysts and Google Engineers participated in the Project.
ESTABLISHMENT OF AGREEMENTS AND OTHER LEGAL INSTRUMENTS
Not applicable.
TECHNICAL DESCRIPTION OF THE SOLUTION
The solution includes the implementation of ORM stages in line with the Business vision of the FACIN
that:

"Describes the structure of the organization's business architecture containing its products,
services, human resources, customers, processes and rules necessary for its execution”.
Business Vision
Structure Description
Business
Capabilities
This describes a business capability and defines what the
organization does, used in high-level vision, and therefore without
the need to detail how, why, or where it is performed.
Services
This describes the tangible or intangible delivered element
constituted through a process of rendering of services to meet the
needs of the customer.
Products
constituted through a production process to meet the needs of the
customer.
Customers
This describes the individuals who consume one of the
organization’s products or services.
Value Chain
This describes the logical groupings of the organization's macro-
processes, at a high level, reflecting the concatenation of business
processes in the generation of customer value.
Organizational
Ontology
This describes the set of business concepts and axioms that relate
such.
Organizational
Structure
This describes the hierarchical map of the organization,
representing the ordering and grouping of human resources into
areas.
Business
Processes
This describes a set of activities that have an objective contributing
to the generation of services or products. It is directly related to
another business process model or an element of the value chain.
Rules
This describes the set of rules that guide the processes and
implementation of the organization's activities.
Knowledge
This describes mastery over a particular topic about something
that has value to the organization.
Skill
This describes the degrees of competence and ability in relation to
determined knowledge that one possesses.
Role This describes the set of duties of an actor.
Actor This describes the organizational position that performs the role.
Figure 8 - FACIN Business Vision Structure
Incorporation of the Machine Learning solution using the following classification algorithms [14] to
predict traditional or exponential activities:
- Decision Tree;
- Random Forest.

Figure 9 – Machine Learning Classification Algorithms
SOLUTION ARCHITECTURE
Capabilities focus on business results. They provide a high-level view of the current and desired skills
of an organization, in relation to its strategy and its environment.
They are accomplished through various elements (people, processes, systems, and so forth) that can
be described, designed, and implemented using Corporate Architecture approaches.

Figure 10: Vision of the Capability-Based Architecture
Resources are a core concept in the field of strategic management, economics, computer science,
portfolio management and more.
Resources can be classified into:
• tangible assets (financial assets, e.g. cash, securities, ability to contract loans, and
physical assets, e.g. facilities, equipment, land, mineral reserves);
• intangible assets (technology, e.g. patents, copyrights, trade secrets, and reputation,
e.g. brand, relationships, culture); and
• human assets (skills/knowledge, communication and collaboration capability,
motivation).
When it comes to human assets, it is necessary to have a properly sized team to meet the demand
with productive and qualified professionals, taking into consideration the restriction of not hiring staff.

GENERAL DEPLOYMENT PLAN
The ORM deployment includes the following stages:
- Qualification of the Demand - Updating of the Services and Internal Services Booklets;
- Capacity Plan - TDABC - Update of the efforts of the teams in the execution of the activities;
- Optimization of Productivity - Implementation of strategies to improve the efficiency of the teams;
- Experience of the Employees - Elaborate the Diagnosis of Training Needs and the Gap in
Competencies of the personnel;
- Effort Dispersal Analysis - Apply Artificial Intelligence and Decision Modeling to identify problems in
the areas and provide solutions.
- Traditional v. Exponential Forecasts - Apply Machine Learning algorithms to identify which activities
should be performed in mode 1 (traditional) or mode 2 (exponential) of Bimodal IT.
- Survey of the BEI Score - Apply the BEI evaluation questionnaires - Behavioral Events Interview
Guide to evaluate workforce competencies and update the forecasts with the actual data.
PROJECT DEADLINE
The project was started in 2015 with the following deliveries expected:
- Drafting of the Capacity Plan - TDABC of the DPR areas in 2015;
- Elaboration of the TDABC Analysis of the Dispersion of Efforts in 2016;
- Creation of the FACIN Environment in the EAD of Prodemge to store the information, in 2017;
- Incorporation of Artificial Intelligence in 2017;
- Elaboration of the TDABC Analysis of the Dispersion of Efforts in 2018;
- Incorporation of Machine Learning in 2018;
- Incorporation of the BEI evaluation questionnaires in 2019
PROJECT COST
Cost of the working hours of the employees involved.
PROJECT IMPLEMENTATION PHASES
The implementation of the ORM stages can be performed in phases following the business vision
structures of the FACIN.

Phase 1
Business Vision
Business
Capabilities
This describes a business capability and defines what the
organization does, used in high-level vision, and therefore without
the need to detail how, why, or where it is performed.
Services
constituted through a process of rendering of services to meet the
needs of the customer.
Products
constituted through a production process to meet the needs of the
customer.
Figure 11 - FACIN Business Vision Structure - Phase 1
With the use of Corporate Architecture, the organization can identify and evaluate its existing or
necessary business capabilities, in order to enable the achievement of its objectives, defined in a
strategy and guided by its governance.
In a simplified manner, a business capability defines what the organization does, without trying to
explain how, why or where it is done. Business capacity may be something that exists today or
something necessary in the future state, with the intention of allowing a new direction or strategy.
When combined, the architecture elements have the ability to represent all the functional and technical
skills a company has at its disposal to execute its business model.
There are structures that describe business functions and services, such as the map of figure 12 that
describes information about all Information and Communication Technology (ICT) services.
Figure 12 - Products and Services Booklet
The functions are presented in the format of a Products and Services Booklet, grouped by towers
according to the category, as can be seen in the Qualification of the Demand stages of the ORM.
The Booklet describes the tangible or intangible delivered element, constituted through a production
process, to meet the needs of the customer.

In addition to the services contained in this booklet, there is a need to map the services that support
the business.
Figure 13 - Business Management and Support Booklet
Phase 2:
Business Vision
Customers
This describes the individuals who consume one of the
organization’s products or services.
Business
Processes
This describes a set of activities that have an objective contributing
to the generation of services or products. It is directly related to
another business process model or an element of the value chain.
Rules
This describes the set of rules that guide the processes and
implementation of the organization's activities.
Figure 14 - Business Vision Structures of the FACIN - Phase 2
The Government aggregates organizations that carry out activities with the objective of delivering
products or services to Society, its main Customer.
In achieving this goal, a good business architecture leads to the improvement of the organization's
systems, processes and results, mainly related to the delivery of products and services to citizens.
The services fulfill a business need of a customer and may be internal or external. The external
services are customer-oriented while the internal services are supportive, geared towards the inside of
the organization.
The internal services, figure 15, describe the tangible or intangible delivered element, covering a
group of activities that are carried out routinely to compose the services provided.

Figure 15 – Map of Internal Services
Internal Services, mapped according to the ORM, can be connected to various types of processes,
such as the processes related to product installation, service management processes (ITIL) or
elements of the Value Chain.
The diagram in figure 16 illustrates the alignment between these elements, arranged in layers forming
a network of connections which, through the transversal integration of information, contribute to the
provision of better electronic services to society.
Figure 16 - Alignment between the Internal Services, Processes and Services Booklet
This systemic view provides greater collaboration and re-use of internal services insofar as their
activities are common to several components.
For this entire mechanism to work in a harmonious way it is necessary to describe the set of rules that
guide the processes and the execution of the activities, registering them in documents that are
accessible to everyone in the organization.

Phase 3:
Business Vision
Value Chain
This describes the logical groupings of the organization's macro-
processes, at a high level, reflecting the concatenation of business
processes in the generation of customer value.
Organizational
Ontology
This describes the set of business concepts and axioms that relate
such.
Organizational
Structure
This describes the hierarchical map of the organization,
representing the ordering and grouping of human resources into
areas.
There are two types of Organizational Structure: formal and informal. Formal Structure is that
presented by the organizational chart where all relations are formal. Informal Structure is the
relationship between the parties outside the organizational chart where the relationships are not
foreseen.
The structural models can be grouped into:
• Traditional: functional, territorial, customers, processes, projects, matrix or mixed;
• Contemporary: networks, inverted, spider web or sunburst.
Figure 18 – Evolution of structures from traditional to contemporary
In order to achieve the objectives, the Value Chain (figure 19) is a graphic representation of how the
company organizes itself to generate value and competitive advantage, that is, it is a set of
interrelated activities that an organization carries out to create value for its customers.
Organizations need to think about their processes as complete entities that begin with a customer
need and end when this need is fulfilled. Ignoring processes, or thinking about processes as things
that happen within departmental silos, is insufficient to promote improved organizational performance
and increase customer satisfaction.

The Value Chain can be broken down into Governance, Business and Support macro processes.
Each macro process consists of processes and sub-processes.
Figure 19 - Value Chain of an IT Company
The Capacity Plan addresses another way of representing the activities. Adapted from Robert
Kaplan's Time-Driven ABC Model, the model maps production capacity to identify the suitable amount
of personnel for the company.
The TDABC model is considered a transparent, scalable, easy to implement and updated
methodology. The model allows managers to obtain important information on productivity, quickly and
inexpensively, by identifying the result obtained by estimating the unit times of the activities.
The primary data survey is performed in all functional areas to identify the activities, figure 20,
according to the service provided.
Figure 20 - Capacity Plan

The capacity plan is based on the matrix of the Products and Services and Business Management and
Support Booklets, grouped by towers according to the category of services.
The services in the booklet are subdivided into internal services, analogous to the Value Chain and its
processes and sub-processes. The internal services are divided into several activities, which support
the study of the Capacity Plan.
In another layer, figure 21, the survey is associated with the needs of Business Process Architecture,
materialized in the Value Chain.
Activities also support the processes of the ITIL - Information Technology Infrastructure Library, a set
of good practices to be applied to the infrastructure, operation and management of information
technology services.
Figure 21 - Activity relationship diagram
The diagram represents the people distributed in the areas of the organization performing activities
related to several elements such as: Internal Services, Services Booklet, ITIL Processes, Value Chain
and Product Installation, in line with the ORM.
Phase 4:
Business Vision
Knowledge
This describes mastery over a particular topic about something
that has value to the organization.
Role This describes the set of duties of an actor.

For people distributed in the areas of the organization to carry out the activities related to the services
and processes delivering value to the clients, it is imperative to have the necessary knowledge.
Knowledge can be achieved in a number of ways, such as in the development of a Domain
Knowledge Document (DCD), an improvement of the ORM.
The purpose of the DCD, figure 23, is to capture people's tacit knowledge and formalize it in order to
be disseminated in the company and acquired by those who will perform service-related activities.
Figure 23 - Domain Knowledge Document Artifact (DCD)
Another important step is the definition of roles, the discriminating elements that differentiate the
individuals based on the duties assigned to them in the organization. The organizational role is based
on the clear understanding of how people should behave and what to deliver at each organizational
level.
People know what to deliver quantitatively, but only the performance of the role will tell them how to
deliver qualitatively. Indeed, it is the organizational role that joins values and standards, culture and
climate, action and intention, short term and long term, economy and development.
It is also necessary to map the teams that will act in the determined centers in charge of the delivery of
the Internal Services.
The knowledge stored in the DCD may be shared among the various team members, figure 24, who
will play the same role, taking into account the productivity of each of them.
Using these documents, the Training Needs Diagnosis (DNC) is elaborated, which allows the
Knowledge Gap of the personnel to be mapped and to plan their training in the short, medium and
long term.

Figure 24 – Map of the Teams
Phase 5:
Business Vision
Skill
This describes the degrees of competence and ability in relation to
determined knowledge that one possesses.
Actor This describes the organizational position that performs the role.
In addition to the knowledge needed to execute the service and process activities delivering value to
customers, as we saw in the previous article, the actors in the organization need to have the
appropriate skills to perform their roles.
Statistics can help us to infer the best allocation of the actors distributed in the areas of the
organization. The normal distribution, figure 26, is one of the most important statistical distributions,
also known as a Gaussian Distribution.
In the Gaussian curve the area in blue is less than one standard deviation (σ) from the mean. In a
normal distribution, this represents about 68% of the set, while two standard deviations from the mean
(blue and orange) represent about 95%, and three standard deviations covers about 99.7%. This fact
is known as rule 68-95-99.7, or the empirical rule, or the 3-sigma rule.

Figure 26 – Normal Distribution
The histogram, also known as a frequency distribution or frequency diagram, is the graphical
representation in columns (rectangles) of a data set previously tabulated and divided into uniform
classes. The base of each rectangle represents a class and the height of each rectangle represents
the amount or frequency with which the value of that class occurred in the data set.
The box plot is a graph that captures important aspects of a data set through its summary of the five
numbers, formed by the following values: minimum value, first quartile, second quartile, third quartile,
and maximum value.
A histogram with probability distribution is used in the display of the values that are most likely to occur
in the verification of the symmetry of a distribution.
The alignment of the FACIN and ORM is materialized in the Demand Qualification and Capacity Plan
phases that address the mapping of the teams that will handle an organization’s service demands.
The survey of the productive capacity of the shared teams is based on the effort necessary to execute
the activities that compose the services, using an adaptation of the Time-Driven ABC Model.
After the team mapping and the effort survey, in a normal situation, the graph of the efforts of the
teams of a given population could have the following distribution:

Figure 27 – Analysis of the efforts of the teams
The degree to which numerical data tends to disperse around an average value is called the variation
or dispersion of the data. The most common measures are: amplitude, variance and standard
deviation.
Amplitude: the difference between the highest and the lowest value.
Variance: a measure of its statistical dispersion, indicating "how far away" its values are in general
from the expected value.
Standard Deviation: the most common measure of statistical dispersion (represented by the sigma
symbol, σ). It shows how much variation or "spread" exists in relation to the mean (or expected value).
A low standard deviation indicates that the data tends to be close to the mean, while a high standard
deviation indicates that the data is scattered over a range of values. The standard deviation is defined
as the square root of the variance.
Among the graphs analyzes of the population above, as they behave as a normal distribution, the
following comparative analyzes can be highlighted:

Figure 28 – Comparative analysis of the Normal Distribution
The aim is to have a small amplitude with a low standard deviation for the efforts of the teams to
remain close to the mean (between 80 and 85% of the effort, according to Kaplan), decreasing the
dispersion.
This objective can be achieved through the Productivity Optimization Model [15] that establishes a
relationship between the demand for services found in an organization and the productivity of the
people in the execution of the activities that make up the service, allowing the best cost/benefit ratio.
In this context, the demand can be distributed to a professional that has the knowledge and skills
necessary to deal with the complexity required, rather than randomly allocating it according to the
criteria established in the qualification of the demand.
Other measures can also be pointed in this direction, as in the diagram in Figure 29, which indicates:
• possibility of automation of low-complexity activities;
• analysis of the need to propose new measures to increase the productivity of teams;
• impact assessment of the optimization of efforts in the performance of the activities.

Figure 29 - Productivity Optimization - The University of Manchester Library
With the implementation of these measures, the DPR resulted in the reduction of the teams' efforts in
carrying out the activities in 11,112 hours, equivalent to 74 people.
OTHER PLANNED ACTIVITIES
Next steps:
 Apply the BEI - Behavioral Events Interview Guide for Digital Workforce Competency
Assessment, prepared by Lily Mok of Gartner [16]. The questionnaire can be applied to three
groups of DPR employees: Top Performance, indicated by HR and people chosen randomly.
 Replace the simulated values with the BEI Score values, run the Machine Learning
algorithms, and check the new predictions.
CONCLUSION AND FINAL CONSIDERATIONS
People are the foundation of organizations, and the right people in the right places with the right
knowledge and skills can increase productivity and deliver more value to the customer.
However, according to Singularity University, organizations are undergoing profound changes
requiring companies to adapt and explore the opportunities and implications of new, exponential
technologies. We need to change the way leaders think about the future by building new capabilities to
arrive there with success.
The use of Machine Learning coupled with the ten characteristics of the Master CIO and the twelve
competencies of the workforce can help lead the Digital Transformations of public organizations from
the traditional to the Exponential as shown below.
Four scenarios have been elaborated starting from the same variables as the ORM simulation, figure
7, but with the actual DPR data, grouping the activities of the Capacity Plan into two groups:

 A Dataset with data of 1,663 activities from all areas of DPR
 Multiple Subsets of cross-activity data with function / task / activity / service area align this
feature with business capability
Aiming to establish the link between how resources are prioritized and mapped to each service (and
associated activities to provision a service) each group is directed to the following value proposition:
 Perceived value by the client: demands of the Services Booklet answered with quality
 Priority: 1 - Value Chain, 2 - Service Booklet, 3 - Strategic Projects
In the Dataset the activities are classified in traditional (0) or Exponential (1), based on the following
criteria: activities of high and medium complexity; pending demand > 0 and Number of people with BEI
Score > 3.
Figure 30 – Spreadsheet with the Dataset of the activities
The business capabilities supported by services / activities are valued by customers (in terms of their
importance and risk of low service performance or large amount of outstanding demand), so the
following Subsets based on the capacity plan were prioritized (figure 21) in this order:
1. Aligned to the Value Chain: Subset of the Network Services
2. Aligned to the matrix of the Products and Services: Subset of the Data Center Services Tower
3. Aligned to the processes of the ITIL: Subset of the ITIL Processes
4. Aligned to the New Services: Subset of the AC Level 1 Project
5. Aligned to the Technological Prospecting: Subset of the Cloud Technology Project
In the multiple Subsets the activities are also classified in traditional (0) or Exponential (1), but based
on the following criteria: activities of high and medium complexity and pending demand > 5.
Figure 31 – Spreadsheet with the Subset of the Network Services
Figure 32 – Spreadsheet with the Subset of the Data Center Services Tower

Figure 33 – Spreadsheet with the Subset of the ITIL Processes
Figure 34 – Spreadsheet with the Subset of AC Level 1 Project Subset
Figure 35 – Spreadsheet with the Subset of the Cloud Technology Project
Scenario A
 In this scenario, the same ORM simulation variables were used.
 The specialist's classification was based only on Pending Demands.
Scenario B
 In this scenario, the variables Ticks and Growth Rate of the Demand were excluded, and the
variable Top Performance (of the best performing employees) was included.
 The specialist's classification was based on Pending Demands and Top Performances.
Scenario C
 In this scenario, the variable BEI (random simulation of the score of the best performing
employees) was included.
 The specialist's classification was based on Pending Demands, Top Performances, the BEI
Score and Complexity of the Activities.
Scenario D
 In this scenario we excluded the Top Performances variable, since we defined the 12
competences as the behavioral characteristics of the individuals who are preachers of
superior performance.
 The specialist rating was based on the Pending Claims, the BEI Score and the Complexity of
Activities.
We can see a considerable modification in the Correlation of Variables between Scenarios A and D.

Figure 36 – Comparison of the Correlation of Variables between Scenarios A and D
When analyzing the Importance of Variables in each of the Scenarios, we can see that by
incorporating the Top Performance variable in Scenario B, it acquired significant importance in the
model in relation to Scenario A. We also observed that the situation changes completely in Scenario
C, with the incorporation of the variable BEI Score, making the analysis quite complex due to the
increase in the number of important variables.
Figure 37 – Comparison of the Importance of Variables between Scenarios A, B, C and D
We can observe that the forecast made by the specialist is equal to the forecast made by the Decision
Tree (DT) algorithm, made from the Subset selected. However, there is a difference between the

prediction made by the specialist and that of the Random Forests algorithm (RFC), based on the
Dataset (all DPR activities).
Figure 38 - Comparison of the Specialist’s Prediction and Machine Learning Algorithms
Once the differences between the predictions have been identified (figure 38), the specialist points out
the problems encountered and discusses the possible solutions with the teams in order to make the
adjustments that they deem necessary and to feed the model into a continuous learning.

Figure 39 – Prediction of Activities (Mode 2 - Exponential) in Scenarios
Initially, some points of attention were identified for each scenario (figure 40), suggesting the
emergence of predominant patterns:
1. Activities that are with the demands met and that are executed by people with high BEI
Score (4 or 5). Evaluate the possibility of training another person to replace it, avoiding
wasted resources (figure 29).
2. Activities that are with the demands met and that are executed by people with low BEI
Score (0, 1, 2 or 3). Work to improve these skills considered low to improve performance
in the execution of the activity.
3. New services, there is no employee allocated to the activity. Capacity building of people
with a high BEI Score in new technologies and redistribution of activities within the area.
Figure 40 - Emerging patterns, problems, and solutions
Here is another example: Here is another example: The prediction of the algorithm (Random Forests -
RFC) in the Dataset is exponential = "Yes" (“activities of high and medium complexity; pending
demand > 0 and Number of people with BEI Score > 3.)”. While the prediction of the expert and the
algorithm (Decision Tree - DT) in the Subset is exponential = "No" (“activities of high and medium
complexity and pending demand < 5.). This will allow managers to assess whether they are not
wasting resources (2 people with high BEI Scores), if they are wasting they can make the necessary
changes (for example allocating one of these two professionals with a high BEI Score to another
team) and replace the values in the Dataset, running the model again and applying supervised
learning.

We can therefore conclude that the amount of activities planned to be executed in Exponential mode
greatly reduces in Scenario C compared to the other Scenarios, which demonstrates the need to
invest in the subjective components (Master CIO and Workforce Competency) in order to achieve
success in the Digital Transformation environment.
TECHNICAL TEAM
Employees from the APR - Infrastructure and Production Directorate Advisors.
REFERENCES
[1] JOHANNPETER, Jorge Gerdau; UNGER, Roberto Mangabeira, O verdadeiro choque de gestão.
Published in Jornal Valor Econômico on 04/07/2009.
[2] PASSOS, G.F.; CHAMOVITZ, I. Modelo De Responsabilidade Organizacional, Aplicado Em
Empresa Pública De Tecnologia Da Informação E Fundamentado Em Dinâmica De Sistemas. In: IX
Congresso Nacional de Excelência em Gestão - CNEG 2013, 2013.
[3] KAPLAN, R; ANDERSON, Steven R. Timedriven activity-based-costing. Havard Business Review,
2004. http://www.hbs.edu/research/facpubs/workingpapers/papers2/0304/04-045.pdf.
[4] ANDRADE, E. L. Introdução à Pesquisa Operacional: métodos e modelos para análise de
decisões. 3rd Ediction. Rio de Janeiro: LTC, 2002.
[5] STERMAN, J. Business dynamics: systems thinking and modeling for a complex world. Boston,
MA: Irwin McGraw-Hill, 2000.
[6] STONEDAHL, F. and WILENSKY, U. NetLogo PageRank model. Center for Connected Learning
and Computer-Based Modeling, Northwestern University, Evanston, IL, 2009.
http://ccl.northwestern.edu/netlogo/models/PageRank
[7] GOVERNO DIGITAL, MINISTÉRIO DO PLANEJAMENTO, DESENVOLVIMENTO E GESTÃO.
Framework de Arquitetura Corporativa para Interoperabilidade no apoio à Governança – FACIN.
2015. https://www.governodigital.gov.br/transformacao/orientacoes/interoperabilidade/governanca-e-
interoperabilidade/facin.
[8] SINGULARITY UNIVERSITY. Preparing Global Leaders & Organizations for the Future. 2018.
https://su.org/
[9] MELLO A.; et al. Are You A Master CIO? Gartner. 2017. https://goo.gl/kGcjfe
[10] BERRY, D.; MOK, L. Develop the Competencies Your Workforce Needs for the Digital
Ecosystem. Gartner. 2017. https://goo.gl/oY46Kc
[11] PASSOS, G.F.; et al. A transformação Digital do tradicional para o Exponencial. 2018.
https://lnkd.in/dqY9mds
[12] SINGULARITY UNIVERSITY. Building Exponential Enterprises. 2018. https://su.org/enterprise
[13] PASSOS, G.F.; et al. Simulation of Organizacional Responsibility Model. 2018.
https://goo.gl/CVW4JR
[14] Kojouharov, S. Cheat Sheets for AI, Neural Networks, Machine Learning, Deep Learning & Big
Data. 2017. https://goo.gl/p2SjrV

[15] PASSOS, G. F.; CHAMOVITZ, I.; THEODOULIDIS, B. Organizational Responsibility Model:
Dealing with Demand for Services Higher Than Installed Capacity. In: 2013 IEEE International
Conference on Systems, Man, and Cybernetics; IEEE; 2013. p. 4415-4420.
[16] MOK, L.; BERRY, D. Toolkit: Behavioral Event Interview Guide for Digital Workforce Competency
Assessment. Gartner. 2017.

Project Organizational Responsibility Model - ORM

More Related Content

Project Organizational Responsibility Model - ORM