3 Business Intelligence Myths
With everyone jumping on the Big Data bandwagon, business intelligence software is needed now more than ever to help make sense of all the information. But BI can be a scary endeavor for many businesses. After all, it’s not only a significant financial investment, but launching a new BI system requires technical prowess and a keen sense of what matters most to the company in terms of performance measures.
Regardless of whether those skills and knowledge come from within or from external providers, business intelligence is surrounded by a lot of myths, half-truths, and misunderstandings that can set your project up for failure before it even gets started.
Here are three myths to be aware of:
BI implementation and user adoption is a one-time thing.
First and foremost, building a business intelligence system means nothing if you don’t get your users on board. People are reluctant to change, even if that change is for the better. Getting an executive information “champion” is the first step to building good user adoption rates. When executives start embracing information, you’ll see that behavior across the enterprise.
Put yourself in your users’ shoes, too. Understand how they work so you can provide information to them in a manner that suits them best. For example, if you’re delivering information to your sales reps on the road, be sure to give them data access on their mobile devices. Also expect a bit of a learning curve and give your users time to adjust to the new system. If the day it launches is the day you expect them to have mastered it, you’re in for a rough day!
Companies can spend weeks, if not months, implementing a new BI system. And once it’s gone LIVE doesn’t mean it’s perfect or that it should be considered another project off the “to do” list. BI needs to evolve over time. There needs to be continuous dialogue between the business community and IT in identifying other requirements, prioritizing them and delivering solutions that address those needs long after the initial roll-out.
Having a data hub will solve all our problems.
BI is often illustrated by diagrams showing many data sources feeding into an enterprise data hub and shiny tools that access data from that hub. While the technology is certainly a key piece of a BI strategy, having it is only 1/2 the battle! Users still need to measure and interpret the data; then take action based on the insights. For instance, sales and marketing teams often have so much data about their customers and products that it’s difficult to cut through the clutter and get a complete picture without a clear understanding of what they’re really looking for. You need to figure out which analytical views of the data will add the most value to your business and your users. Fortunately, there are pre-built BI applications on the market that provide such views out of the box — putting data clearly into perspective for those who need it.
BI ROI is hard to measure.
You cannot manage what you cannot measure, right? Well the whole point of business intelligence is to make it easier on your business to measure and better manage performance. From studying customer buying patterns and the effectiveness of various sales initiatives, to better inventory management and improved forecasting efforts, business intelligence software gives you the ability to manage, measure, and track all kinds of data. Measuring the ROI for BI programs may be difficult, but it’s not impossible.
Gartner analysts recommend that businesses measure BI ROI by looking at user satisfaction with the relevancy, accuracy, consistency and timeliness of data being used to make decisions. Ask yourself, and your teams, “Do I have the information that I need to better manage my business?” Are you using real data to make decisions as opposed to relying on best-guesses?
Another way to measure ROI is to consider the risks/costs of not using your BI system once it’s been implemented. After all, it costs money to store, secure and archive the gargantuan amounts of data floating around a typical enterprise. If you aren’t using that data to improve internal processes your BI system is just another expensive tool left gathering dust.
When all else fails, consider this fact from a recent study by Nucleus Research: Organizations earn an average of $10.66 for every dollar spent on analytics. You can do the math!