Answer Three Simple Questions to Get Started
For most business owners and organizational leaders, the term “data analytics” has become standard (arguably essential) lingo in recent years. Although most savvy leaders easily recognize the importance of using data to understand historical results, identify current trends, and predict future outcomes, it can be very challenging to take the first step toward becoming a data-driven organization.
To help alleviate the pressure of trying to create a large-scale, long-term data analytics program, which can be incredibly overwhelming, businesses can start by introducing data analytics using a more practical day-to-day approach. For those who are ready to take the first step, answering three simple questions can provide the jump start they need to begin harnessing the power of their business intelligence.
These questions are: What? Where? and How?
The first step in becoming a data-driven organization is to identify what information you want to measure and analyze. What are the performance indicators that you look at to track progress, success, weaknesses, and areas of opportunities? What challenges or barriers do you currently face? What measurable information would be most valuable to your operational leaders on a day-to-day basis to help them make faster, more well-informed decisions?
Once you begin thinking about all the “whats” that you could measure, it can become overwhelming to narrow your list down to those that matter most.
Key tip: Set your sights on the “quick wins”—the one, two, or three measurements that will provide the most actionable insight to your business at the current point in time.
Once you have identified what you want to measure, the second question you must answer is, “Where?” Specifically, “Where is your data located?” Internal data sources would include your operational systems and applications, such as customer databases, accounting software and financial statements, point-of-sale transaction logs, inventory management reports, etc. In addition to your internal data sources, also consider any external data sources you could utilize that could aid in decision-making. For example, industry data that is available through open data repositories and government portals.
As you begin exploring the answer to the question of “Where?”, you may be surprised by the number of data sources you uncover.
Key tip: Once you identify your data sources, be sure to create an inventory list, or documentation, for future reference. At a minimum, include the name of the data source, the data available within it, who has permission to access the data, and (if known) the data format/structure.
Now that you have identified what you want to measure and where your data is located, you are ready to tackle the final, and possibly most challenging, question: “How?” How will the data be combined and presented in order to provide the insight you need? Depending on the complexity of your data, you may be able to utilize your current resources, such as Microsoft Excel, Google Sheets, or the built-in dashboard functions of your existing applications. However, in most cases, business data is complex and you may choose to seek outside assistance for data extraction, organization, and visualization.
Key tip: Remember that your business intelligence is a substantial asset—unlocking the insight it can provide is an investment in the success of your company’s performance, competitive advantage, and strategic direction.
HBE is Here to Help
HBE’s data analytics services help clients realize the true value of their data by unveiling insights that can move their business or organization forward. Whether identifying sales patterns or developing visual representations of financial performance, our goal is to provide clients with actionable information and guidance to improve productivity, gain efficiencies, and fine-tune their competitive advantage. Please contact us if you would like more information on how we can work together to harness the power of data analytics within your business or organization.