Madison Partners LOGO Negatief
Transform your business foundations


The road towards a data-driven company is a complex journey. Culture, organizational structure and business processes are often a bigger challenge than technology.


Uncertainty and change have become the new normal. Organizations now need to embrace change in their culture and operating model if they want to thrive in an uncertain and rapidly changing world.

Alignment between

the technical and business


Getting alignment between
the technical and business world

A lot of companies experience a huge gap between data science and business execution. The business is not aware of all that is possible with data/AI and solutions that are developed don’t fit the need.

Insufficient results

with data and AI initiatives due to resistance in the organization

Insufficient results

with data and AI initiatives due to resistance in the organization

People do not always trust data & AI due to insufficient involvement and knowledge.

A cultural change is required when moving from a few Proof of Concepts to operationalizing data & AI.

Growing complexity has made processes heavy and slow

Growing complexity has made processes heavy and slow

Established companies are often organized in siloes for efficiency reasons. In the digital era, the value chain requires close collaboration across different departments and a different alignment of incentives. Business processes are not designed for rapid experimentation

Three-quarters of CEO's expect their organization to change more over the next five years than it did over the past two decades.

"A transformations towards a data-driven company is not just a technology project,

it requires new ways of working and thinking."

Thomas Dubois, Head of Business Transformation


Transforming the operating model is a major challenge, especially for established companies. There are many different paths and many different starting points to become a data-driven organization. Nevertheless, all successful transformations share common elements: 

  • Becoming data-driven starts at the top. Although the entire business is involved, we ensure that management buy-in is available. This is an essential prerequisite to kickstart the transformation.

  • Data is often scattered around the organization. An understanding of the data value chain is key to change the operating model and underlying governance structure. We involve every one in the organization and strive for a new way of working where siloes are overcome.

  • All the people involved need realize what lies ahead. This often requires a cultural change. Data-driven decision making should become a part of the company's DNA: if there's no adoption, there's no value. We anticipate this resistance to change and proactively manage this.

  • Processes must be adjusted to embrace changeWe work towards agile delivery with rapid learning & decision-making cycles, involving the necessary decision makers.

  • The transformation requires to take a broader view in sourcing and identification of required skills in the organization. Our approach includes evaluating data proficiency of the current workforce, in order to translate analytics and data-driven insights into business decisions.


    • We facilitate an ongoing conversation between executive decision makers and those who lead data initiatives in the organization.


    The enterprise architecture of the future is lightweight and solid at the same time. It will rely on rich data insights to make decisions and to move quickly in order to respond to a dynamic, global business environment. As a result, traditional flows to design your applications and standard enterprise architectures won’t cut it.


    Becoming an ‘experimental enterprise’ means transforming the way you operate on a fundamental level. This means embracing agile approaches, laying the foundation for a ‘fail fast’ technology platform and, of course, investing in the right technologies – but don’t panic, it always starts on a small scale


    A resilient operating model

    Establishing a strategic planning process that occurs more frequently: six-month planning horizon with quarterly reviews to support greater agility. The governance model includes regular reflections from execution back into the vision and strategic direction.

    Faster results

    An Agile way of working that supports cross-functional teams to collaborate in short test-and-learn iterations. By equipping the team with an 'experimental mindset', faster results can be obtained with less likelihood spending too much effort on solutions nobody needs.

    Aligned acountability between business & technology

    By linking data initiatives to business objectives, and supporting the organisation in understanding the added value of data and AI.