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Unifying an Enterprise Through Master Data
Unifying an Enterprise Through Master Data
From sharing data between functions and locations
To data as a common ground for enterprise unification
To data as a common ground for enterprise unification
Master data can be described as valuable data that is shared across an organization. The transition of data becoming master data is a continuous process. But once data becomes a master data it flows through an enterprise and is used by many users in multiple functions. I propose any data can become master data, depending on the time and place in an organization. Transactional and analytical data from one process is master data for the following process.
Not an ocean: an Archipelago
If you consider the flow of master data, an enterprise and its value chain would resemble an ocean. Data ripples through the water and touches all the other data around it. However, for an organizational perspective, this is an ideal situation which is difficult to attain.
Enterprises and their data are usually structured into a group of islands. Some islands may be connected by fairways, while others only have tiny bridges that may or may not have a ‘cross at your own risk’ sign. Of course, there are also islands that want nothing to do with the outside world.
We cannot emphasis much on the necessity of structuring an organization. While dividing an organization definitely adds multilayer benefits, it may also induce certain boundaries and limitations on having overall picture. Responsibilities, goals, and objectives are set within the boundaries of the island (enterprise/company/functions/branches/country). These might fit the needs of the island but may have unwanted effects on the whole archipelago.
Risks for Clustered Enterprises
There are several risks for enterprises that cluster their responsibilities and data. Most of these risks relate to troubleshooting and missing out on opportunities.
1: Missing signals from other clusters
Issues in an interconnected value chain affect the entire process. A problem in one part of the chain may have unwanted effects on processes that occur later or simultaneously.
2: It is hard to solve issues that span across clusters
If all clusters in an enterprise, or clusters across enterprises, do their own thing, it is difficult to standardize and analyze problems. This includes security issues and data integrity issues. When all clusters speak a distinct language and use different methods, it is very time-consuming, if not impossible, to get everyone on the same page.
3: Valuable data can go missing in action
As clusters filter their data and pass on only parts of it (or none of it), valuable information gets lost. Clusters will start searching for data that has already been gathered and disposed of in other parts of the organization, using up valuable time and resources.
4: It is hard to make fact-based improvements without unwarranted effects
Improving the value chain piece by piece is always an option, but the repercussions of changes remain unclear until they are included in the bigger picture.
Advantages of shared Master Data
Sharing relevant data may reveal unwanted effects of one cluster’s action on the other. It opens up the conversation and enables preventive measures. Master data can be the common ground where clusters meet and start solving issues on a larger scale.
An enterprise-wide approach to master data will also result in valuable insights into which data is used where and how. An industry-wide approach would be even better. This will reduce the time needed to gather information and enable constructive sharing across the board. An enterprise/industry-wide approach will enable better decision-making and changes that benefit the entire organization.
Uniting the Enterprise with Data
The advantages of sharing data are quite clear. But how can data really unify an enterprise? I believe it starts with people. Master data is, by default, an overarching concept. The conversations about data and data sharing can be a great way for clusters to get to know each other and start sharing within and across enterprises.
Sharing master data, of course, but also sharing insights, experiences, and enthusiasm. People will appreciate the hard work of other companies and departments that result in valuable data for their own activities.
Of course, there will be people who feel that data should be the responsibility of the IT departments. They will have to realize that data holds valuable information that can benefit their operations and make their life easier.
Working towards patient-centric value chain
When clusters have opened up and communication has started, new possibilities arise for the enterprise and the life science industry. Clusters can stop being islands with separate goals and start discussing the most important end goals: those that benefit the patients.
Louis Hendriks (CEO,Global Value Web)
Louis Hendriks (CEO,Global Value Web) shares his vision on master data as a unifying factor for enterprises in life sciences.
Enterprises in life sciences like to cluster their activities in branches, locations, or departments. This may be practical, but it also inhibits constructive changes that benefit the whole value chain. Sharing and discussing master data may be the uniting factor.
Global Value Web is a network of data experts and technology partners that allow organizations to make the most out of their data. We offer valuable insights across the value chain that will lead to more efficient production processes and reliable quality products. We focus on a better execution today, while keeping in mind the challenges for tomorrow. With our shared knowledge and expertise, we prepare your data flow for a bright and profitable future.
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