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Fixing the foundation first: master data

In October 2020, Midagon released the white paper How to drive business value from digital in process and manufacturing industries. In that white paper, I discussed the importance of fixing the foundation first as an integral part of digital or data-driven new business capability development.

In this blog post, I will continue that discussion by explaining what should be taken into consideration in modern-day master data management and how it contributes to building and deploying new data-driven and digital business capabilities.

Let's begin with the ‘good-old basics’ first. I see master data as the vital fuel that feeds the core business processes implemented on top of the ICT systems of a company. If the quality of that fuel is bad or if the fuel tank is empty, the machine will fail - and so will the processes. Following this example, master data management, in turn, is a set of governance models, processes and tools to make sure that the fuel is constantly in good shape and available for the set of machines to use it and to enable the critical business processes.

From a business perspective, master data management is extremely important for two reasons: First of all, it has an impact to business analyses and decision-making on the operational and strategic levels. Master data is used extensively to drive the transactions of a company and if the core input data is missing, poor in quality or not reliable, the subsequent business analyses and the operational decision-making based on the data from transactions will potentially lead to wrong interpretations and decisions. Sooner or later, this also becomes an issue on the strategic decision-level.

Master data also has an impact on business operations. For example, all sales, supply chain and service operations are based on good quality master data and if - for one reason or another - this input data is unreliable, missing or poor in quality, it can lead to costly operational mistakes. For example, if the customer master data is not up to date, a company could easily send spare parts to a wrong ship-to location or an invoice to a wrong legal entity.

From a digital services perspective, poor or missing master data is a killer. For example, analyses or advice given to a customer to adjust the settings of a machine or to stop the process based on poor master data could lead to costly litigations or even safety incidents.

From a development project perspective master data is equally important. In order to deliver new business capabilities successfully, there has to be a clear linkage between the business strategy, operating model and business processes as well as the integrated systems, data flows and valid data. If any of those building blocks is missing or neglected, it means that the whole capability will most likely fail.

As discussed above, the importance of master data and master data management should be very obvious for all companies building digital and data driven capabilities. For one reason or another, this unfortunately is not always the case. Perhaps it is related to the very nature of master data management being traditionally fairly technical in nature, resource intensive and time consuming and the fact that master data management does not implement any new business capabilities per se – it enables them.

At Midagon, we believe that master data management is one of the core foundational capabilities that a company must possess to plan, prepare and operate during the digital era. Consequently, we have recently updated our master data management related methodology.

Our approach to master data management is modular and can be applied to small, medium and large-scale companies with different maturity levels in MDM.

First of all, our approach emphasizes the importance of understanding the true business needs, issues and priorities for master data and master data management: what master data domains and entities are critical for the company and why? What are the current master data related issues and what is the business impact?

Second, we believe that it is extremely important to create a clear situational awareness picture of the current status of relevant master data domains and master data management from the governance, processes, data quality and architecture perspectives.

Third, we believe that the TO-BE solution for master data management should match the organizational capabilities of the customer company and consequently take into consideration limitations and expectations towards resourcing, ongoing development initiatives and the available set of tools & technology. Finally, our methodology focuses on creating a realistic, stepwise implementation and deployment roadmap for change that splits the journey into manageable iterations that yield to tangible benefits and allows adjusting the course, should it be needed.

As the interest towards foundational capabilities - including master data management - is growing, we will continue with this topic in our upcoming interview in the Wapice IoT Lab Episodes. Stay tuned for more information!

For more information about our foundational capabilities and MDM methodology, please get in touch at jukka.kauppinen@midagon.com!


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