Organizations across industries are expressing increased interest in data strategy. For many organizations, the initial reaction is to focus on the data itself; in reality, the data is only a small portion of what is important in a data strategy.
Many IT and line of business leaders are surprised to learn the best place to start when creating a data strategy is not data but the business. Identifying areas of your business that depend on sound decision-making is a great place to start. The leaders who are shaping an organization’s data strategy should get to know the people and the processes already in place. Who is making decisions? What information are they using to make decisions? What happens after a decision is made?
Questions That Can Improve Your Understanding of the Data
This knowledge helps you to understand where potential areas for improvement may exist. It’s important to take a look at where decision-makers draw their information from.
Consider these key questions when trying to gain a better understanding of how your decision-makers interact with information:
- In what format is the information delivered? Is it through an Excel report or maybe a dashboard? Can the decision-maker manipulate this information, or is the information static?
- Is the information accurate? Can this information be trusted, or are there known discrepancies?
- Is the information timely? Information loses its relevance as it ages. When the time comes to make a decision, will the data be up to date?
- Is there enough context around the information to avoid unnecessary risk, delays and inaccuracies?
After understanding the gaps in the current processes, you can determine how to apply technology advancements to shore up the decision-making process. Let’s dig into the areas of format, accuracy, timeliness and context a little further.
The Elements of Deeper Data Discovery
When it comes to information delivery, the modern trend is visual analytics with a focus on self-service tools. While Excel reports have their strengths, they have limitations as well. Staring at tables of information is not how most people prefer to determine what’s important in a data set. Providing decision-makers with tools that allow them to manipulate what they’re looking at and how they’re looking at it can go a long way toward examining the complex variables that go into making a decision.
It should go without saying that information accuracy is paramount to making sound decisions. However, many decisions-makers end up relying on information that is less than accurate. Reconciling multiple versions of the same information that don’t exactly match introduces a variance that can profoundly affect the outcome of a decision. Putting measures and tools in place to increase data quality is crucial to the execution of a sound data strategy. It’s also important to understand that improving data quality is not a one-time exercise; it’s an ongoing process. Developing a framework under which you review the quality and accuracy of your data will allow you identify and correct inaccuracies as they come up.
Timing and relevance are closely linked when it comes to using information to make a decision. Being armed with outdated information or having to make a decision while waiting for updated information can be risky. Alleviating bottlenecks in access to data, whether they may be technical or personnel-based, should be a top priority of any good data strategy. Making decisions today on yesterday’s information can render your decisions irrelevant. While real-time data receives a lot of attention, even increasing access to information that is hours old as opposed to days old can have a substantial impact.
Context is king when it comes to decision-making. Looking at the temperature outlook for the day doesn’t provide much help in deciding whether to bring an umbrella. You need the full weather forecast. Business decisions are no different. The more information you can arm yourself with, the more fine-tuned your intuition will become. Whenever possible, it’s best to consolidate the number of data sets a decision-maker has to consider. No one wants their office wall to look like a scene out of a crime thriller, with a maze of thumbtacks and red yarn piecing together information. As data analysis solutions trend toward self-service tools, this consolidation is now more possible than ever.
Data strategies don’t have to be elusive. Focus on your people and processes before you focus on your data and technology, and your data strategy will begin to develop. Focusing on your data and technology first might leave you with a data strategy that never sees the light of day.
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