Data-driven Digital Transformation
Data-driven Digital Transformation

Nowadays, everyone agrees that in this technological era, digital transformation is an inevitable and continuous process for businesses. Establishment of data-driven business analytics in the company automatically results in commencement of data-driven digital transformation, which is tightly connected with five main areas of business operation:


  • Interaction with consumers



  • Business model and organizational structure


  • Product, its production and supply chain



  • Processes and management systems
  • Technologies and IT infrastructure




Sometimes, establishment of consumer centric analytics starts spontaneously and without understanding full measurements, it can become a reason for failed attempt. Switching from product-centric business model to consumer-centric business model is a strategic decision of the company which ultimately starts with change of mindset and formation of a new vision.


We help companies prepare and successfully implement data-driven digital transformation. Our approach is based on PWR3® concept, where any stage of transformational process is reviewed in three main dimensions: vision, culture and enforcement.


Working Approaches 


Working process of data-driven digital transformation comprises of 7 stages. Each stage is multi-component and considering the company’s progress in terms of transformation, it may last from 6 to 24 months:

Realizing the need of data-driven digital transformation arrow

Transformational process starts with realization of needs. Client is usually an initiator of making changes, but from expressing very first though to thorough understanding, initiative requires multi-dimensional revision in order to understand the benefit and see bigger picture before making any specific steps. ACT’s consultants can make significant contribution in the process of realizing needs – by understanding external visions and potential challenges related to data analysis.

Organization’s digital diagnostics arrow

Studying the current digital environment and comprehensive understanding is an important phase of data-driven digital transformation. This is when consumer-related data collection, processing and analysis chain is transmitted to human, technological and operational perspective. As a result of diagnostics we get full picture – where the company is, what needs to be done to effectively plan and implement intended transformation.

Formation of transformation leadership team arrow

Transformation team unites those leaders who are responsible for planning required changes in the organization, making decisions and enforcement of these decisions. ACT’s consultants help client in terms of defining configuration, forming and building the leadership team. This is when real transformation starts in the company because leadership team purposefully focus their energy and resources on changes.

Development of strategy and vision of data-driven transformation arrow

On a road of changes, one of the important steps is to re-think visions and strategy in the perspective of data-driven transformation. In some cases, initiatives result in renewal or change of the business model. Decisions made on this stage shape contents and form of transformation.

Action plan and establishment of the mechanism required for monitoring arrow

Over the course of this stage, ACT’s digital transformation team helps the client develop an action plan corresponding with the set strategy and visions, assess required resources and establish criteria required for monitoring of the process. This completes the planning part and large-scale digital transformation starts in the company.

Organization’s digital diagnostics arrow

Studying the current digital environment and comprehensive understanding is an important phase of data-driven digital transformation. This is when consumer-related data collection, processing and analysis chain is transmitted to human, technological and operational perspective. As a result of diagnostics we get full picture – where the company is, what needs to be done to effectively plan and implement intended transformation.

Allocation of resources and getting organization ready for transformation arrow

In the majority of cases, it becomes necessary to update the current system to support data-driven digital transformation. In addition to this, new positions often emerge which requires allocation of the existing staff or recruiting new talents. ACT assists client in allocation of “right employee to right position”. Getting organization ready for transformation implies collaboration of the working team and correct positioning of visions and set goals to them. ACT’s consultants will work with every stakeholder who is directly involved in establishment of customer-centric analytics or is a beneficiary of its results.

Enforcement, monitoring and correction arrow

Finally, in compliance with the set goals and action plan, the company enforces establishment of data-driven digital products. At this final stage, ACT’s main role is to facilitate quick and effective decisions related to transformation processes.


In addition to this, in terms of the specific digital product, ACT business analytics team can help the company select supplier, plan works and conduct monitoring.

In addition to data-driven digital transformation, in enforcement part, ACT offers establishment of customer centric analytics and BI tools.


Our project management methodology is based on the golden standard of the industry (CRISP-DP – Cross-Industry Standard Process for Data Mining) which is actively applied when managing Data Science and Machine Learning processes and comprises of 6 phases:


BU (Business Understanding)


(Modeling)

Understanding data processing goals and business tasks.


Analysis of data structure, quality assessment and description of exchange mechanism.


DU (Data Understanding)


(Evaluation)

Data organization, processing, formatting and unification.


Choosing the technique, building the model and generation of test design.


DP (Data Preparation)


D (Deployment)

Evaluation of results, Alpha testing, planning integration in unified system.


Beta model testing, integration in unified ecosystem, development of monitoring and system maintenance plan and full deployment in the product.




Together with standard process, project team is guided by agile approaches based of which works are divided into short-term sprints. Concentration on each spring makes gives a feeling of success to the team which boosts motivation and expectation towards the following stage. But in some cases, it happens that we go back if needed, we go back to the previous process and go through it again, more thoroughly. All of this is done in order to achieve the best results.

Product