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Data-driven transformation

Data-driven business transformation and its three cornerstones

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Martin Rydman, Enfo


Presumably, the data in “data-driven” must mean timely, correct and useful data. Everybody who works in IT knows that the challenges of having such data available are daunting. 

My initial aha-moment prompting this meditation on the perennial problem of data quality came in the opening paragraphs of a book I’m currently reading: “Non-invasive data governance” by Robert S. Seiner. He simply asks us to consider this question: What cannot your organization do because of invalid, incomplete and incoherent data? This is an excellent question. He suggests some answers and I’ve added some of my own:  

  • We cannot compare costs across regions 

  • We cannot maximize the position of products in the store 

  • We cannot match the touchpoints of customers across all our channels 

  • We cannot apply resources in the most cost-effective way 

  • We cannot maximize our decision-making capabilities based on the data we have 

  • We cannot bring new digital services to our customers 

His purpose in posing this question is to provide the reader with a strategy to “sell” data governance to top executive stakeholders.  

I will take this insight as a segue to the next question: How can we provide timely, correct and useful data? I will stitch together three things that you might want to consider simultaneously.  

I believe all three are vital to tackle the exponential onslaught of data and secure the revolutionizing potential of data-driven business transformation: 

  • API-led integration 

  • Master Data Management 

  • Center for Enablement 

API-led Integration

API-led integration is the process of connecting data and applications via APIs (application programming interfaces). It allows integration flows to be defined and reused by multiple parties inside and outside of the organization. API-led iIntegration is both a way of working with application and integration development and appropriate technologyies to enable it. 


Master Data Management

To make these APIs truly reusable, they must expose and process the core entities of your business (such as products, customers, vendors, employees, facilities, etc.) in ways that are relevant to the business processes and not based on the internal database schemas and processing logic of the systems that store and process them. They must also cater to evolving business needs, not least the burgeoning App landscape, where more and more actors repurpose their own and other’s data to provide new services and revenue channels. Defining these reusable data integration points requires Master Data Management. Master Data Management is both a governing discipline and enabling technologies. 

Center for Enablement

The final piece is Center for Enablement (C4E). A few years ago, we talked much about Center of Excellence (CoE). The CoE model provides all expertise and resources needed to convert business requirements into working solutions. This has become increasingly untenable as the business requirements have increased exponentially. The C4E model focuses on: 

  • Providing clear and actionable API and MDM visions and strategies 

  • Providing guidelines, blueprints and best practices 

  • Establishing, supporting and managing API and MDM platforms 

  • Supporting and accelerating consumer-led development initiatives 

The goal for a C4E is not to develop and support solutions but to enable and support various teams (which the term “consumer-led development” implies) to build and run their own solutions with enough guardrails to maintain a coherent application landscape with well-defined and reusable APIs that provide data and functions aligned with the business processes.


How to get started

Modern data management is a tall order whichever way you look at it. But considering these building blocks from the outset will provide you with a high-level road-map. Fleshing them out will still have to be done in an agile, opportunistic and fail-fast fa shion. But maybe you can bring on board at least a handful of experts to get a C4E started. One seasoned MDM guy and one seasoned API guy would go a long way, provided top-level stakeholders are willing to initiate a strategic initiative, not only a project, and plan and allow for the C4E team to grow as the need for it grows. Also, at least one of them must fully understand the C4E concept, lest they immediately slip into more of a CoE operational model. 

Hopefully, these thoughts have got you thinking in new ways around the concept of data-driven business transformation. I’d be happy to take the discussion further if you found them interesting. 

Martin Rydman is a business excellence lead at Enfo 
+46 70 567 9702