Do you have a data strategy?

In a world of digital ecosystems, data is the raw material that fuels the digital economy. In order to be a part of this value creation, there is a need to have a clear data strategy. How does one go from the traditional approach to collection, storage and reporting to strategic use of data?

In the past data was a necessary byproduct of existing processes and activities, and has slowly through the evolution of functions like CRM gained tactical value in numerous organizations.  Data went from being stored in the data warehouse for safe-keeping, through use of business intelligence for reporting and analytics towards real-time use of data in providing customer value.

Another distinction between past and present is the evolution from focusing solely on internal data to looking beyond the boundaries of the organization for relevant data through open APIs. The amount of data at hand has also grown at an exponential rate and is expected to grow even more as everything around us result in some kind of data output. As the amount of data grows at a rapid pace, so does the complexity regarding the use of data.

If things weren’t complicated enough, business-critical data usually correlates with privacy and personal information, meaning that it is imperative to stay compliant to data privacy regulations like GDPR as well as maintain bank-grade security for everything that contains personal data.

The first step towards making sense of this landscape is appointing someone responsible for designing and implementing your companies’ data strategy. Traditionally, data ownership is distributed across organizational silos, but the true value of data becomes actionable when you look beyond organizational structures and view the company as a whole. Ownership of a data strategy should not be based on data origination, but on the ability and necessary skills to make sense and take action based on available data.

However, hiring a bunch of data people and give them access to play around with the data may be a good starting point in order to get a feel of the raw materials at hand, but will not make the boat go any faster.

Define the aspirations for use of data in your organization. What is the purpose of your data strategy? Are you seeking to gain customer insight and predictions that are more precise? Are you aiming for better operational efficiency through the use of sensory data in your production processes? Are you looking for a way to monetize data through new business models? The various possibilities are limitless and there is no one size fits all when it comes to data aspirations.

In order to lay down the groundwork, you should map your existing data sources and have a well thought out plan on how to collect, update and store your data. When do you need real-time data, and when is it good enough with a good old-fashioned overnight batch? The freshness of the data should also govern you overall principles of data storage and accessibility. Make sure you make sufficient use of your existing data before starting to collect external data. The more data you have, the bigger the complexity.

If data is the raw materials of your digital strategy, APIs are the pipelines that provide those materials. Make sure your platform is able to handle data exchange through both internal as well as external APIs.

No matter your aspirations and well thought-out data strategy, data is only valuable if data quality is accurate. Data quality need to be based on a single defined source of through, and just like the overall data strategy, someone needs to be accountable for data quality and governance of all time. Poor data quality could result in systemic errors if injected in machine learning algorithms or automated processes without proper human supervision.

In summary, a data strategy should (at least) consider the following:

• Define clear goals and aspirations
• Make sure you have the necessary skills
• Stay secure and within the boundaries of regulations
• Data quality is a key prerequisite
• Map your data sources
• Have an active approach to the necessary freshness of your data
• Make use of the data you already have before hoarding additional data
• Define clear KPIs and metrics for success

For companies that wish to stay relevant in an age of changing customer behavior and increased competition in the digital space, becoming data driven is crucial. Having the right data and a clear understanding of how to utilize those data enables your organization to make the right decisions based on facts and insights rather than gut feel and assumptions.