Digital Transformation and the Impact in Knowledge Management

Gabriel Petana

and Carlos A. Rosa

UNIDCOM - Faculdade de Design, Tecnologia e Comunicação da Universidade Europeia, Lisbon, Portugal

Keywords: BizDevOps, Context-awareness, UX Engineering, Decision Support and Data Analytics.

Abstract: Nowadays, digital transformation is forcing companies to reach a new level of productivity and digital

evolution. Small and autonomous is winning over large and centralized. Digital transformation requires the

adoption of more agile business processes and the development of new customer-facing digital services. It

means creating scale through reusable services and enabling self-service consumption of those services.

Business processes and transactions can be automated with the composition of microservices. We will see

that the principle of composability allows microservices to deliver value to the business in different contexts.

The paper also explains how a BizDevOps philosophy with references to microservices allows rapid

adaptations of requirements to fast-changing needs in businesses, outlining the importance of business process

automation for companies to acquire the know-how to implement a just-in-time diachronic dialogue. It

presents the alignment of the proposed framework with a digital strategy. Assembling a multidisciplinary

team is foreseen as a key factor in developing innovative capabilities to react to new customer demands,

enabling the company to stay competitive and continuously address customer expectations, differentiating

tacit from explicit knowledge.

1 INTRODUCTION

In the past ten years, companies felt the need to

digitize their business operations and establish a

business unit dedicated to building and operating

customer-oriented digital services. As companies

create and expand their digitally transform, they need

to unify data, processes, coordination, and

measurement of the moving parts that make up a

modern, omnichannel customer experience (Ermine

2013). Hence, many companies foster the automation

of internal processes to become more competitive.

It means creating cross-functional teams where

the team members share problems, solutions, and

tools to (re)think not only how to address customers’

needs but also to (re)design existing business

processes. The emergent tendency is to build

BizDevOps teams for the ideation, creation,

development, and operation of new digital services

(Chasioti 2019). The concept is being introduced by

more and more companies to create smaller

empowered teams and to break down the borders

between people traditionally associated with

https://orcid.org/0000-0001-6916-2575

https://orcid.org/0000-0001-5733-523X

Business (Biz), Development (Dev), and Operations

(Ops) departments. The lack of communication and

cooperation between these people has promoted the

creation of knowledge silos, causing the company

inefficiencies and business opportunities not well

explored because of underexplored synergies

between the three teams.

The BizDevOps team has an agile mentality and

adopts a small-scale, highly focused team framework

to rapidly innovate on defined units of business value.

They are responsible for continuously (re)defining

the business for certain (micro)services and

monitoring customer experience/satisfaction. In the

digital economy, the BizDevOps team has a high

degree of autonomy in designing the functions and

architecture of microservices, and therefore

contributes to business-IT-alignment in a new way.

The implementation of a BizDevOps philosophy with

references to microservices requires the adoption of

an effective “digital enterprise architecture”.

In this paper, we present a framework named

Matryoskas Sequence for Knowledge and Innovation

(MATSKI). This framework provides a holistic view

180

Petana, G. and Rosa, C.

Digital Transformation and the Impact in Knowledge Management.

DOI: 10.5220/0010134001800187

In Proceedings of the 12th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2020) - Volume 3: KMIS, pages 180-187

ISBN: 978-989-758-474-9

 2020 by SCITEPRESS – Science and Technology Publications, Lda. All rights reser ved

of supporting the transformation of raw data into

knowledge, using it in an eective manner to

generate a sustainable competitive advantage in the

knowledge economy. The framework was

scientifically funded on an integrated modeling

sequence for organizational management and just-in-

time transformation for a competitive, efficient, and

valuable performance in the market (Rosa and

Pestana, 2019).

Consumers continue to raise their expectations for

products and services. Therefore, the ability to

convert data into embedded knowledge is currently

considered a valuable intangible asset. In this field,

the possibility of providing decision makers with

contextual insights about stakeholders’ perceptions

and attitudes is a key concept to meet customer

expectations and improve business performance and

competitiveness at all levels. Knowledge

management and innovation seem to be axial

paradigm of the development of the digital economy

(Malhotra, 2001; Gloet and Berrell, 2003; Nilla and

Kemp,2009, Rosa and Pestana, 2019), and the

survival of business models that are interested in

analyzing and understanding the market’s perception

of a specific product or brand.

This introduction is followed by section 2, in

which we outline why companies felt the need to

digitally transform their business operations,

establishing fast digital business units dedicated to

build and operate digital customer-facing

microservices. Section 3 describes the

methodological approach we employed by presenting

the theoretical framework associated with the

MATSKI, including a detailed presentation of two of

the business processes within the proposed

framework. Finally, in Section 4, conclusions are

presented with an outlook for future work.

2 THE IMPACT OF DIGITAL

TRANSFORMATION IN

BUSINESS COMPETITIVENESS

2.1 Multidisciplinary Teams and

Microservices

With digital transformation, two concepts have

emerged: microservices and BizDevOps. Both are

practices designed to provide greater agility and

operational efficiency. Research on business

architecture that uses a BizDevOps philosophy and

refers to microservices to support product

digitization, outlines the formation of

multidisciplinary teams to achieve common goals and

jointly develop innovative capabilities with a single

functional view to respond to the needs of new

customers in order to stay competitive (Drews 2017)

- digital disruptions. Therefore, meeting customer

needs is an ongoing challenge that requires constant

innovation to retain and maintain customer loyalty.

As shown in Figure 1, we will have a BizDevOps

team when the developer team and the operations

team work with business personnel throughout the

project development cycle. Having such a multi-

disciplinary team aligned with the business line it

supports, we can use agile thinking to meet the

specific needs of customers, save money, make

business models more stable, and make people

happier and more productive (Forbrig 2017).

The BizDevOps approach can facilitate

collaboration and communication between managers,

business analysts, and development teams to build

new business models to enhance interaction with

customers. However, BizDevOps can only work

when the right people, processes, and technology are

involved. Thanks to this technology, real-time data

analysis (i.e., just-in-time) can also be provided for

business processes, enabling collaborative workflows

to create continuous delivery pipelines, which puts

forward new requirements for maintaining

operational excellence. And the realization of

enhanced or new (digital) business models with

higher quality and lower risk

According to the literature (O’Reilly, 2018;

Kotler, 2017), there are a few dominant

characteristics for the new business models in the

digital economy: (1) companies with separation of the

production means (e.g., access instead of possession);

(2) use of technological platforms for knowledge

management and interaction (24/7 co-creation and

dialogue); (3) a variable geometry service and prices

(algorithms adjust supply according to demand); and

(4) custom work subcontracted to measure.

There are some notorious illustrative examples: Uber

revolutionized transportation and food delivery,

WhatsApp broke the foundation of messaging and

communication, AirBnB revolutionized the

accommodation and leisure economy, RedBox

changed video and media rentals, and Netflix became

a major player in the entertainment industry, Lyft

leads the American demand-car company, Farfetched

is the top online luxury fashion retail platform; Glovo

has become the leading fast door-to-door delivery

service for small goods; Amazon is the world’s most

delivered company; Google, Instagram, Dropbox and

Slack are huge world communication platform

leaders, etc.

Digital Transformation and the Impact in Knowledge Management

181

Figure 1: The difference between a traditional and a

BizDevOps approach, adapted from (Schrader 2018).

All these examples apply new business models

(competing with traditional models), and are

supported by a build-to-order or Just-in-time

(knowledge sharing and transformation) management

model, with “zero” stock and a substantial increase in

the operational efficiency and business profitability.

In this case, innovation is strongly generated from

users in a permanent (24/7) dialogue, and the lead

users (i.e., early users, domain experts, opinion

leaders and influencers) become the “core engine” of

this diachronic flow of co-creation (creative

intelligence).

The participation of these users potentializes the

discovering of the “golden nuggets” (e.g., best

innovative ideas and concepts) to feed new business

processes with lower costs, which can be afforded by

SMEs and micro-organization. In this area, it is

foreseeable that continuous innovation is a

sustainable process that can support the response to

new requirements and changing market demands, and

establish new business models to empower customer

interaction.

Since customers are more demanding than ever

before and will abandon businesses that are too slow

to respond, all businesses strive to provide an ideal

customer experience. The microservice-based

architecture shapes the delivery of solutions to the

business in the form of services, thereby providing a

holistic and unified omni-channel customer

experience. Companies that adopt microservices,

together with a BizDevOps philosophy, share

common approaches to the role of the technology in

providing decision-makers with the right tools and

information they need in their daily business

operations (MuleSof 2016). As such, identifying and

defining digital assets that are align with core

business capabilities is critical.

A microservice that encapsulates core business

functions and comply with usability design principles

to promote a smart user experience should be

regarded as true digital assets. Positioning

microservices as a valuable asset of the enterprise

implicitly promotes the adaptability of microservices

and enables them to be used in multiple contexts. The

same service can be reused in multiple business

processes or on different business channels or digital

touchpoints as needed. By applying the principle of

loose coupling, the dependence between the service

and its users can be minimized. Adopting this design

method (i.e., microservices encapsulate the functions

of a specific business domain) helps other

groups/applications to discover these

(micro)services.

The principle of composability allows aggregated

services to create value for the business in different

contexts. The addition of data analytic techniques

also helps to bring value to the business, because it

enables the service to be used in a variety of

situations.

Microservices are interoperable in nature.

Because their interfaces are defined according to

existing standards at the industry level, they facilitate

the exchange of information regardless of how they

are implemented. If microservices use standard

protocols (such as RESTful API) to expose their

interfaces, they can be used and reused by other

services and applications without direct coupling

through language binding or shared libraries.

2.2 Total Quality Management

Theoretical Framework

The design method can also benefit from a Total

Quality Management (TQM) ideology to build

potentially shippable product increments, which

speeds the deployment pipeline, achieving a result

that culminates in bringing changes to production as

quickly as possible and in line with customers´

expectations. Organizational development and

transformations should be applied under a TQM

framework (Yusuf, 2007; Talib, 2013; Rosa 2014),

aiming to meet full customer satisfaction and

recommendation and higher business performance

and competitiveness at all levels.

Furthermore, it can be observed that (...) the high

competitive level of the market ... implies the

development of technical quality management

systems – also designated TQM (Total Quality

Management) - in which technological systems of the

dynamic type of collection can be integrated by

information modules with feedback and/or dialogue

(...), (Rosa, 2014).

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TQM has been extensively discussed in the

literature … as a management philosophy

characterized by its principles, practices, and

strategies that emphasizes upon continuous

improvement in quality, increased involvement of

employees, the commitment of top management,

employee empowerment, teamwork,

benchmarking, leadership, rewards and

recognition, feedback and relationship with

suppliers (Talib, 2013).

The implementation of the TQM framework

should thus consider three fundamental operational

aspects: (1) commitment, (2) involvement, and (3)

continuous improvement. Commitment as a never-

ending (e.g., diachronic) improvement process for

quality and services delivery to the customer;

involvement of all the team members in achieving a

common goal; and of continuous improvement by

monitoring and correcting any error and defects on

the spot (i.e., just-in-time).

3 THE KNOWLEDGE

MANAGEMENT VALUE CHAIN

3.1 The MATSKI Landscape with

Digital Strategy

In this section, we present the MATSKI

framework

(Rosa e Pestana, 2019), a holistic framework that

supports the transformation of raw data into

embedded knowledge. The simultaneous

management of tacit knowledge and explicit

knowledge helps to transform the organizational

knowledge in the diachronic knowledge flow, in

which learning, sharing and interaction are the basic

functions, which can continuously acquire new

knowledge and consolidate existing knowledge,

thereby bringing a strong competitive advantage to

the organization. In this knowledge flow process, it is

important to distinguish between tacit form explicit

knowledge. Generally, tacit knowledge is defined as

embedded in individuals (i.e., not documented

possessed by an expert), and explicit knowledge is

defined as existing in documents, books of rules,

databases and other record formats (i.e., well-

documented).

Inspired by the Matryoskas concept - or Russian dolls

metaphor. Also referred in the literature as the “matryoshka

scientific principle”. This is a technique to adapt, enhance

or create new processes when needed. The principle was

originally used in the computing industry, where systems

This holistic, integrated framework empirically

confirms the parsimony of a collaborative

multichannel communication flow (e.g., a just-in-

time diachronic dialogue) with customers and the

stakeholders (e.g., suppliers, distributors, and

employees), encapsulated within the basic

operational aspects of the TQM framework and

controlled by performance metrics (e.g., just-in-time

KPIs), synchronized with the gathering of new

knowledge obtained by data semantics, context

awareness analysis, and visual data analytics,

originated by the co-creative interactions that reveal

the most valued insights – designated as the Gold

Nuggets.

From a high-level perspective, the MATSKI

landscape consists in three conceptual pillars:

Processes, Technology, and People’s skills

operationalized by (1) an ontological model for the

Processes pillar; (2) an operational model for the

Technology pillar; and (3) an applied model for the

People’s Skills pillar. The knowledge value chain

presented in Figure 2 provides a knowledge

management (KM) framework to analyze the value

added by each KM process. In this chain, information

is the result of data processing, knowledge is the

result of information processing, and wisdom is the

result of knowledge processing. The objective is to

provide an analysis and action framework that will

make it possible to act on the value chain and improve

the company’s performance, gradually steering the

company toward greater cognitive capacities.

The digital strategy endorses digital governance,

which is fundamental to define a clear responsibility

of aligning the role of the BizDevOps team with the

company policies, business (digital) services, and

customers’ expectations. This alignment is essential

to create competitive advantages and future value-

added for the stakeholders. Digital governance, when

effectively defined and implemented, will for sure,

help the development of digital and agile business and

sustainable company (Welchman, 2015; Almarabeh,

2009). Figure 2 represents the fit of these overall

strategies. The InovaFlow (an ontological meta-

system) maps how tacit knowledge is captured to

diachronically feed the creation of (new) explicit

knowledge and transform it into (new) embedded

know-how.

and processes can be built inside one another, but it can also

be adapted to modelling an organizational or business

model.

Digital Transformation and the Impact in Knowledge Management

183

Source: Ribeiro, R. (2020)

Figure 2: The alignment of the MATSKI landscape with digital strategy.

The Organizational Knowledge process deals

with aspects for processing explicit and implicit

knowledge integration, and for embedded knowledge

updating. The Consumer Knowledge process is

relevant for capturing life stories and narratives, for

stakeholders learning, sharing, and interacting, and

for the development of Community of Practice and

living labs for ideation, development, and testing of

new products/services. The Market Knowledge deals

with the environmental and benchmark of

competitors. It is focused on serving customers in

ways that are differentiated from competitors,

creating a unique user experience. In section 3.2, a

detailed collaboration diagram is presented for the

two (first) process of the InovaFlow.

A digital strategy aligned with business process

automation enables companies to acquire the know-

how to convert digital value propositions of their

businesses into revenue-generating digital offers

(Ross, 2018). One way to achieve this goal is by

promoting cooperation and dynamic interactions

between business units. As outlined in section 2.1,

microservices are intrinsically interoperable. They

facilitate an exchange of information independent of

how they have been implemented. If microservices

expose their interfaces with a standard protocol, such

a RESTful APIs, they can be consumed and reused by

other services and applications in a simple and

automated way. That means they will optimize their

internal operation functions, to engage new

experiences to customers. These experiences are able

to create unique emotional relations and new views of

loyalty between the customer and the company in a

continuous operation referred to as optimum market

value function.

3.2 Business Process Management

Automation

Mastering business processes for new products or

services development, and how they must be adapted

for end-users and just-in-time management, have

become key elements in achieving competitiveness in

modern companies. In this domain, the automation of

business processes is emerging to a semantic

paradigm, modeling, and implementation approach. It

is considered to be one of the most valuable assets for

organizations since its management appropriation

helps companies to quickly adapt their business goals

and structures to environmental changes while

maintaining or improving their competitiveness

(Ross, 2018).

These are the many reasons why business process

management (BPM) is becoming so important. BPM

represents a disciplined approach to “working” with

automated and non-automated business processes in

order to achieve consistent and targeted results that

are aligned with an organization’s strategic goals

(Ribeiro, 2020). As such, BPM roles are usually

related to business roles, such as domain experts and

data analysts. But, it is also important that technical

roles, like developers, should be involved in

managing activities within business processes, as

process models provide a good point of

communication between all the participants in the

process workflow.

In order to be understood by a BizDevOps team

and become interoperable between IT tools, BPM

must be based on standardized notations that are

usually symbol-based or graphical. A well-designed

business process diagram, which is based on a

standardized notation, such as Business Process

Model and Notation (BPMN), can positively affect

most BPM activities and improve both intra- and

inter-organizational communication as well as

fostering collaboration.

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BPMN 2.0 is a notation that uses standardized

symbols to denote events, activities, tasks,

connections, etc. Once a process is specified by

articulating ‘who’ does ‘what’ including the

interaction with others – the BPMN is able to

explicate the dynamic structure of an organization

based on existing functional components and

facilitates specifying novel organizational behavior

patterns. This notation must be learned by the creators

of the workflow in order to enter it into a system.

Figure 3 presents how the Organizational Knowledge

and the Consumer Knowledge processes from the

MATSKI modelization were implemented using

BPMN 2.0 to model the information workflow and

interaction between the team elements participating

in each process.

The MATSKI provides a practical framework for

managing the company’s knowledge, providing a

dynamic Just-in-Time flow for continuous

improvement and innovation of the business model.

As outlined in Figure 3, it is central to any digital

strategy the deployment of a Knowledge database (K-

Vault) where the reported information is saved as a

Knowledge Object. Each Object is searchable and

reusable in a multitude of ways. Once in place,

Knowledge Objects can be shared with other

members, or with other teams - embedded knowledge

sharing. In this case, microservices facilitate an

exchange of information. They have a key role in the

workflow for situational-awareness, keeping the

BizDevOps team informed about any “golden

nuggets” the system might identify (resulting from

the cognitive analysis and the data analytic tasks).

Figure 3: Collaboration diagram for A) Organizational Knowledge process and B) Customer Knowledge process.

Digital Transformation and the Impact in Knowledge Management

185

It is also understood that knowledge partners can

increase understanding and may contribute to

embedded knowledge updating. Therefore, multiple

knowledge partners (K-Partner) continuously feed

the system with additional information (DO1); this

information needs to be classified and analyzed based

on an existing business rule or inferred know-how

derived from new knowledge objectives (K-

objectives) which may retroactively update the

company embedded knowledge, and consequently

triggering new actions. This dynamic, just-in-time

management of the company K-Vault operates on the

promise of empowering companies to capture and

repurpose their unique (tribal) knowledge that is so

often and easily lost. The K-Vault is different from

previous works on automatic knowledge base

construction as it combines noisy extractions from K-

Partners with prior knowledge, which is derived from

existing knowledge bases. A knowledge base

combines extraction from Web content (obtained via

analysis of text, tabular data, page structure, and

human annotations). With MATSKI it is employed

supervised machine learning methods for fusing these

distinct information sources. The Consumer

Knowledge process enables an approach to specific

Communities of Practice (CoP) and use of technology

(e.g., Chatbot and innovative graphical voice-based

interfaces; interactive dashboards and omnichannel

awareness mechanisms) to promote interactive

dialogs with knowledge customers (K-Client) to

capture the market perception and/or to

perceive/anticipate customers preferences, interests,

and needs. The process is focused on interactions,

structuring communication between the parties

defining in which sequence messages are received or

sent, and how internal actions are executed.

However, according to the MATSKI ontological

meta system, knowledge about subjects and their

interactions needs to be elicited in the course of future

research. The goal is to gain a knowledge-driven view

of the business processes that need to be in place to

support the MATSKI workflow both within and

outside the organization. We need to focus both, on

streamlining organizational and technology

development in order to coherently address the

mental, conceptual, and technological layer. The

mental layer embodies the shift of mindsets towards

concurrent interactions. The conceptual layer is

required to establish corresponding models (i.e.,

implementation-independent representations), while

the technical layer captures infrastructure to be set up

for acquisition, representation, processing, and

distribution of the embedded knowledge.

4 CONCLUSIONS

Digital transformation requires the adoption of more

agile business processes and the development of new

customer-facing digital services. For many

companies, the digital modeling of their own

processes still ranks as a major challenge that takes

much time and involves in-depth coordination

between subject-specific departments and the IT unit.

This paper outlines the need for companies to adopt a

digital strategy and how organizations can help their

stakeholders becoming more engaged in driving

competitive advantage framed by or based on,

adopting a BizDevOps approach (i.e., the integration

of domain experts with development and operational

teams), with a convergent vision on establishing new

business models to empower customer interaction. A

BizDevOps approach can facilitate collaboration and

communication between management, business

analysts, and development teams for establishing new

business models to empower customer interactions

and knowledge sharing and learning.

As companies create and expand their digital

presence, they need to unify data and processes,

coordinate and measure all moving parts that make up

the modern, omnichannel customer experience.

Hence, many companies foster the automation of

internal processes to become more competitive. A

microservices architecture shapes the delivery of

solutions to the business in the form of services,

providing a holistic and uniform experience to the

customer across all the business channels

In digital business, customers are more willing to

try new options than ever before. New competitors

may bypass established companies in a short time

with little or no indication they were a threat until they

show up on the customer’s doorstep. This means that

the digitalization of the business, as well as shorter

innovation cycles and changing customer demand,

resulting in new requirements for maintaining

operational excellence as well as to enable enhanced

or new (digital) business models.

The paper presented the MATSKI framework as a

holistic framework that supports the transformation

of raw data into knowledge in an effective just-in-

time manner. The corresponding knowledge value

chain was introduced to examine and analyze the

activities of knowledge management that are seen as

a key factor in realizing and sustaining organizational

success for improved efficiency, innovation, and

competition in the digital economy. In such a

knowledge-based approach, it is important the

distinction between explicit and tacit knowledge. The

Organizational Knowledge process and the Customer

Knowledge process were both described in detail

using a BPMN collaboration diagram. They define in

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186

which sequence messages are received or sent, and

internal actions are executed. The introduction of

advanced modeling features reflects the capability of

BPMN to capture complex business cases while

ensuring operational coherence, promoting

interoperability for business process automation.

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