Who are your customers? How much does it cost to acquire a new one? Which customer relationships are the most profitable? The least? Can you evaluate your high-level business performance and seamlessly drill down to a granular transaction, shipment or customer account? If you can’t answer these questions, or you find yourself looking for answers in the seemingly endless rows of Excel spreadsheets, it is time to consider a business intelligence solution.
Business intelligence, data analytics, big data and similar terms have been used so indiscriminately in marketing materials, their true value are often lost on business owners. Business Intelligence (BI) solutions provide visibility into all levels of the business and transform data from an operational byproduct into a competitive advantage.
Many businesses have separate systems for financial reporting, inventory management, relationship management, payroll, time, warehouse and social media management. Even when many of these functions are contained in a single integrated ERP system, reports often include gaps and only paint a partial picture.
This, however, does not mean that executives are doomed to incomplete, imperfect oversight. A forward-looking strategy helps organizations achieve visibility into their operations and give executives the information they need to make successful decisions.
Business Intelligence isn’t “all or nothing,” nor is it a discrete project. A proper BI initiative is an iterative process of understanding the data produced by an organization, accessing and manipulating relevant information to drive business decisions based on the actionable insights, and incorporating the results of those decisions as additional data streams. There are many ways to do BI correctly, and there are ways to turn the initiative into a calamitous misadventure. Below are five recommendations for your success:
- Understand what you want. It is easy to drown yourself in data and become encumbered by analysis paralysis. Determine what insights are most relevant and work backwards, figuring out what data needs to be analyzed to get there.
- Start small, scale large. Crawl > Walk > Run. Business Intelligence is often an iterative process, and works best when broken down into phases with recursive improvement. Trying to go from zero to 60 all at once can often lead to oversights, missed deadlines and resource burnout.
- Understand statistical fundamentals. Most people who work with data have heard the phrase “garbage in, garbage out.” This means that if the data you analyze is not valid, then the analysis and decisions you produce will not be valid either. The same applies for statistical sampling rules and experiment design. If I try to analyze a sample of 10 transactions, it will not representatively extrapolate to the sales over my next 5 years.
- Describe, predict, prescribe. A successful digital strategy extends far beyond descriptive analytics and data visualization. Predictive analytics allow businesses to leverage their historical data and predict future outcomes. Prescriptive analytics take descriptive data, predictive data and a set of goals and constraints to make data-driven, optimal business decisions. This can be as simple as a linear program performing inventory routing, or as complex as a machine-learning-based AI offering customers personalized shopping incentives.
- Listen to the data. Often, it is tempting to use data to corroborate our conclusions, justify our decisions, or reinforce our desired course of action. These temptations often lead to biases which can undermine the entire purpose of a business intelligence initiative. The numbers don’t lie—follow them wherever they lead you…do not try to make them fit your mold.
If you are interested in simplifying your company’s BI assessment process, RSM offers a Business Intelligence Rapid Assessment, a quick-hit diagnostic tool that will provide you a complete analysis of your data analytics options and a custom report including recommendations based on your organization’s strategic priorities. Email me directly at Louis.Higgins@rsmus.com if you would like to learn more.