Exploring the added value of a data platform: a business case

Oct 26, 2021
  • finance
  • data

In our blog on the benefits of data platforms, we explained how a data platform really helps CFOs to see the full picture of what’s going on across the organization. As the proof of the pudding is in the eating, let’s look at a fictional customer case: the story of an organization that wants to lift analytics and reporting to the next level – and decides to build a data platform to do so.

The case: the CFO of a large, rapidly expanding international logistics company wants to step up its financial reporting in order to give the management a consolidated, more detailed view of the finances at all its sites. While the available ERP platform helps to consolidate financial data and report on these, it doesn’t provide enough details to gain a full picture. After all, the organization uses a plethora of systems and tools, spread across the organization.  

Profitability modelling

The first to-do on the CFO’s list is to run a customer profitability analysis to get a better view on net profit margins. As the profit and loss statements in the available ERP platform do not include enough details on all the operational and logistic costs on the customer level, they need to build a profitability model. 

A profitability model combines a large volume of operational and financial data with a number of business rules. That data, however, is not easily available at our organization, as it uses many separate systems that are not integrated into the ERP backbone. After a first analysis, the project team discovers they need six different data sources to build a relevant model, which are spread across the ERP platform, and three systems that are managed and maintained by the Operations, Sales, and Logistics divisions. 

On top of that, the master data at hand are inconsistent. The number of customers and their segmentation, for example, differ between the different systems, as do the product data. Even in the finance team itself, it is hard to get one version of the truth. Different team members, for instance, export data from the ERP system using different filters – which leads to different results. 

Thanks to a series of master data mapping exercises and some extra efforts in terms of ETL, the project team manages to build a profitability model that combines all the selected data. To make sure all the hard work pays off and minimizes maintenance efforts in the future, the CFO made sure the model was set up in such a way that it can be leveraged should the organization move towards a data platform in the future.

With a data platform, all the data from the most diverse sources would be centralized, ensuring one version of the truth. The finance team would have access to consistent data that is relevant for any use case.

Building one central reporting tool

As a next step, the CFO decides to combine the profitability reporting with reports from ERP and operations. By combining insights from finance, operations, sales, and logistics, they’d get an end-to-end view on performance management as a basis for more solid business decisions.

To achieve this aim, different data sources have to be brought together into one central reporting tool – another technical challenge. A new mapping exercise is required, now in terms of reporting categories.

At this point, it has become crystal-clear that a data platform would bring substantial added value. The CFO, as well as the rest of the organization, realizes the importance and potential value of data to support new insights or innovative ideas, and understands that they need to unlock the data for use in the entire organization. More than data delivery, a data platform would also receive and consolidate data from all modelling use cases and open them up for the reporting tool(s).

a data platform is a must to get one version of the truth and, as such, gain an end-to-end-view on the business reality. As a result, discussions are much more strategic, focusing on adding value to the business instead of on data quality, consistency, and governance  

One version of the truth

The decision to build a data platform brings a wind of change to the organization. All the company data is now integrated in a central data platform that different departments can easily interpret, because master data and categorization are gradually being synchronized. Every new use case – from an ad-hoc analysis to adding a new division or even a newly acquired subsidiary – now leverages the efforts made in the platform and leads to results faster.

So, the company now continuously expands its data platform with data that they didn’t need in the past, but which are important for getting the entire organization covered.

With the data platform, all the data are now instantly available in the data platform and later on in the models, for every new use case – ready for the finance team to gain insights from it.

The need for cultural change 

In addition, the organization works hard to instill the cultural changes needed to get the most out of the data platform. In the past, departments created and managed their own data, with their own tools, policies, procedures, and databases. Moreover, they were pretty reluctant about sharing data to avoid misinterpretations. As a result, data were not only heavily siloed, but there were also many discussions regarding their accuracy and interpretation. Teams spent hours questioning the data source instead of discussing the real operational issues. 

Everyone at the organization now agrees that the data platform is a must to get one version of the truth and, as such, gain an end-to-end-view on the business reality. As a result, discussions are much more strategic, focusing on adding value to the business instead of on data quality, consistency, and governance.  

Do you also feel like siloed data creates barriers to insight in your organization? Get in touch with our experts to discuss the value of a data platform for your company.

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