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Is your project financial report showing a different number compared to the one published by PMO? (or) Have you seen the global learning team’s summary differ from that of your In-Country training unit’s report? Sounds not unusual, right? Btw, why is it taking place? I am sure you recognise this. It is happening because these reports are extracting data from disparate data sources which are not in sync with each other.
In the above example, you know one of the reports is incorrect and hence you can take corrective action. However, that is not the case always. Sometimes, you do not even know the data silos exist. Data silos are not good for the organisation. But what is a data silo? Why does it happen? Let us discuss this in this article!
Data Silo:
Data that is captured and stored in a database/file, which is not part of the enterprise data architecture, is called a data silo. The data silo doesn’t interact with other applications in the organisation, making it difficult to recognise its existence at the enterprise level.
Why does it happen?
Data silos are created because of the following 6 reasons.
1. Lack of enterprise-wide data strategy
Enterprise-wide data strategy talks about technologies to be used, and processes to be followed to capture, store, and share data. The lack of an enterprise-wide data strategy is a common reason for data silos.
2. Organisation Structure
Decentralised business units function as independent entities. Each of them has its own IT strategy and budget. This might cause data silos because of the below reasons:
2.1. Decentralised IT procurement decisions without considering the bigger picture create disparate data stores.
2.2. Integrating the new tool with enterprise-wide systems is not a priority for the decentralised teams.
2.3. The Skillset of the IT team members varies from one business unit to another. The lack of skilled resources to integrate data could be one of the reasons for data silos.
3. Limitations in Technology
If you encounter limitations in technology, it is difficult to integrate the data. Hence, once you capture the data, you leave it disintegrated. This goes back to point-1 of not having an enterprise-wide data strategy.
4. Culture of the organisation
1. Data sharing in a controlled manner must be in the organisation’s culture.
2. Sharing is not overhead: - If your project team considers sharing as an overhead to the project, you will create a data silo as a by-product of the project delivery.
3. Competing priorities: Business units having competing priorities typically don’t share as they see it as a threat to meeting their objectives.
5. Group Chief Data Officer
CDO must have equal say as the CIO in big transformational projects. CIOs typically see the data silos as technical debt. In a bigger schema of things, we create tech debts considering other priorities. But data silos are much more than a technical debt, as the data that is captured is not being used for the benefit of the organisation.
6. Growth of organisations
Organisations grow through mergers and acquisitions. The acquired entity must be using a different database to capture and store data. As part of the mergers and acquisition strategy, integrate the IT systems of both entities. Until you integrate completely, data silos will exist.
Hope this gives a bird’s-eye view of what are data silos. As you can see, most of the reasons are non-technical and can be well-addressed by decision-makers in the organisation and it’s not easy.
Thanks for reading. I have made a conscious effort to minimize the usage of jargon and focused on concepts. Please share your views in the comments section.
The content of the article is based on my views and in no way reflects my current and previous organizations and vendor partners.
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