Just having business data and the means to analyze it doesn’t guarantee a business benefit. The process of getting from data to decision is nuanced and riddled with potential pitfalls like dirty data, ambiguous results, institutional skepticism, and more. The right analytical process, however, will help you turn information into insights and make game-changing decisions for your company.
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What is Business Intelligence?
It’s important to set the table when using terminology that might be muddled by marketing. Business intelligence is one of those terms that companies and business leaders use interchangeably with a lot of other related terms, so the original intention might get lost. Let’s be clear: business intelligence includes all of the diverse technical architectures used to support the collection, analysis, and presentation of information important to a business.
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So while you might think of BI as the study of certain analytical practices, some might associate the word with a type of software application. In the simplest terms, business intelligence can be used to describe anything related to the analysis of business data.
Data Driven or Analytics Driven?
Lots of companies will claim to be focused on the data they have and might even use phrases like “data-driven decision-making.” When a company says they are data-driven, what they really mean is that the analytics — not the raw data — are what drive their decision. Data is nothing more than information without context. Businesses rely on data to provide the skeleton of their strategies, but it’s the analysis that makes the muscles move.
How Can Business Intelligence Lead to Business Decisions?
There is a steady supply of software designed to help businesses turn information into insight. Some things to look for in your business intelligence solution are data blending (aggregate data across sources), ease of use (this is especially vital if users have varying levels of technical proficiency), and a light organizational lift (how much time will your IT department need to devote to these systems, and do they have the bandwidth?). Exago BI is an embedded BI solution that checks all the boxes, with seamless integration, user-friendly dashboards, flexible self-service reporting, and comprehensive support. No matter how you gather your intelligence, these are the steps to using it to make decisions.
Step 1 — Data Acquisition
Before you can make decisions, you need the data, and the data has to be analyzed before it can be implemented. There are two sources of business data: external and internal. Internal data is generated by the company itself, including customer information, inventory supply, logistical data, buyer personas, etc. External data comes from sources outside of your organization. Either source is enhanced and informed by the other through the implementation of business intelligence, usually through BI software. Gathering all of your data in one place is a great start, but you’re not quite ready for Step 2 yet.
You have to ask yourself two questions:
- Is my data dirty? An important part of the data preparation process is making sure that data is clean. The old saying “garbage in, garbage out” applies especially well when it comes to data hygiene.
- Is my data accurate? It sounds like an obvious corollary to the above, but when you’re accessing data from multiple sources, it might not always agree. This is a great opportunity to define a single source of truth.
Step 2 — Data Analysis
How this analysis happens is important to consider and amounts to more than simply looking at which direction the lines on a graph are moving. The right BI will give you the tools you need to do exploratory analysis and root out correlations, but will also provide a framework for evaluating the data (benchmarks, for example). Without context, you’re stuck looking at info in a vacuum. A good BI solution will also provide users across the org chart with analytical tools appropriate to their roles. Some may only ever read canned reports while others might want to modify those reports or even create all-new ad hoc reports from scratch. Meeting users where they are is key to ensuring analysis gets done.
Step 3 — Application and Execution
Once data is collected and analyzed, it’s time for execution. Analysis of the data will provide signposts and insights, but they’re useless without action. For example, your analysts might tell you about how a previously untapped population of potential customers could be worth targeting. Spending money and time on a new venture backed by solid data analysis is much easier to justify both to yourself and to stakeholders. Don’t be afraid to venture to places you hadn’t considered before. After all, decisions informed by business intelligence add a reliable layer of accountability that other decision-making processes might not have. When it comes time for execution, act only when you’re sure you’ve explored possible blind spots and biases.
Step 4 — Assessment
If you’ve implemented those decisions and maybe even tried some new strategies that you would never have considered before your intelligence-gathering, it’s time to measure its success. Be both patient and objective when drawing conclusions from past performance. Don’t base your actions on statistically insignificant figures or jump to conclusions about causality. Document your assessment so that you may later refine your reasoning with the benefit of hindsight.
Obstacles You Should Expect
Don’t expect the movement from intelligence to decisions to be smooth–even with the best business intelligence analysis in the world, you will encounter snags. Some issues to look out for:
Data Illiteracy
This could be an entire post on its own. Fluency with data, analysis, tools, and implementations is not something you should expect from everybody at your organization, but basic data literacy is an altogether different proposition and a much lighter lift. The value of a data-literate culture company-wide pays dividends when everybody is aligned on how to process data.
Institutional Skepticism
Expect pushback, especially around inconvenient findings. Stakeholders may cast doubt on your analytical process in order to avoid difficult decisions or minimize bad news. The more rigorously you follow the steps above, the easier it will be to convince skeptics that your analysis is sound. With any luck, this skepticism will dissipate after the solutions prove themselves.
Analysis Paralysis
If you’re reorganizing your entire decision making apparatus to incorporate business intelligence, it can be tempting to rely on it for everything your business does, against your better judgement. Don’t become so dependent on data analysis that you ignore your instincts. Business analytics should supplement your decision making process, not completely replace it. Also be wary of analysis paralysis — your conclusions might be ambiguous, and even the best data analysis can’t answer every question.
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The Road is Not One Way
It’s important to remember that through all the potential pitfalls, complications, challenges, and obstacles, the decisions you make have to inform the data you collect. It might seem like an obvious conclusion, but the pressure of immediacy can make the future look a little fuzzy. By using business intelligence to inform and focus business decisions, you can make the best choices at the right times to maximize their utility.
