Business intelligence has changed the way we run businesses. With analytics tools, you can know things as they happen, make informed decisions on the fly, and do away with old-fashioned reporting. You can give everyone in your company a 360 degree view of your organization, your customers, and your opportunities. However, it’s not as easy as spending a bunch of money on a BI tool. You’ll need to take a hard look at your data, your systems, and your people. Here are a few steps you should take to prepare for business intelligence.

If you’ve already seen our post “How to prepare your data processes for analytics,” this post will refresh your memory, and give you an idea of the steps that come after. Check back for more detailed articles about each step in this process.

1. Understand Your Data

Bad data leads to bad analytics. The first step in preparing for Business Intelligence is making sure your data is reliable. Take stock of all the data sources in your organization. Examine how you capture data and look for ways to improve the process. For example, if you can replace human data entry with a machine, it’s usually a good idea. If that’s not possible, give people the time and resources to enter data properly. Your employees should take data capturing as seriously as you do.

Now that you’ve captured some data, verify its accuracy. Set up redundant data capturing processes, compare your data to third party sources, or perform a data audit every month. Sniff out errors in your data and correct them before they spoil the whole bunch. If errors keep showing up in the same places, you might want to look at how you’re capturing that data.

Lastly, consolidate your data, and agree on a single source of truth. If possible, get your data in one place. It doesn’t have to be a single machine or database, but there should be some thread that ties all your data together. Without a way to compare different data sources, your analytics will take longer and won’t work as well. If consolidating or integrating your data isn’t possible, you should at least decide on a source of record for each form of data. Employees need to know where to turn. If there’s confusion, everyone ends up with different data. If you’ve ever been in a meeting where everyone has a slightly different copy of the same report, you understand the need for a single source of truth. You can’t get on the same page when everyone’s looking at a different page.

2. Understand what to measure

All knowledge is valuable, but you need to prioritize it. What are your company’s Key Performance Indicators (KPIs)? What do you absolutely need to know to run your business? Who needs to know it? Beyond the basics, what’s a metric that could really help the business? It takes some thinking, but this is where you’ll find the keys to better performance. Your KPIs are the basis for all of your analytics, and a little thinking now can save you a headache later.

Start by listing your most important KPIs. Typically, these are the metrics you’re using before analytics. Not every company uses BI, but every company knows their revenue. Your first priority is to account for the KPIs you already use day-to-day or month-to-month. 

Once you know which KPIs you need to have, think about what you want. Analytics opens a big door to new metrics, and new ways to examine your business. Make a wish list of KPIs that interest you and your coworkers. That said, don’t get too ahead of yourself. While it’s okay to plan, don’t expect to have every last KPI nailed down before your deployment. Furthermore, don’t plan on making reports for every last KPI on day one. Most of our customers find it works best to measure basic KPIs at first, and worry about advanced reports and KPIs down the road. An iterative approach gives you time to get acquainted with your BI tools. It also saves you from spinning your wheels on a KPI or report that sounds more useful than it is.

3. Understand your audience

Advanced KPIs and analytics can reveal game-changing information about your business, but only if your audience knows what they’re seeing. Furthermore, you don’t always know what sort of analytics people need, especially if you never ask. Your average manager probably knows their way around a line graph or a histogram, but they’re not the only people who can benefit from analytics. Indeed, many of our happiest customers say they get the most of analytics on the floor of their factories or warehouses.

In order to address a less technical audience, you need to think about their needs, not just what you want them to see. For example, a factory worker probably doesn’t have time to fiddle with a mouse and keyboard, so you might want to build a more passive analytics dashboard. Talk to people, and learn how they do their jobs. Ask them if there’s a metric they could use to make their job easier, faster, or more convenient. Without a solid understand of what your audience needs, you may build charts no one likes, and end up wondering why no one uses them.

4. Understand your systems

Most companies use more than one software system to run their business. Between ERPs, CRMs, and everything else on IT’s plate, it can be a challenge to know where things are, and how everything works. You should understand your company’s systems so data can be placed where it’s needed. Standard reports can come from out of the box, and they’re valuable for daily reference. However, unless your systems and your data are properly structured for analytics, you won’t get as much out of them as you could.

For example, a neck tie company using NetSuite might have a data set with separate fields for tie length, and tie material, but all the data about each tie’s color, pattern, and width ends up in a “notes” section. As you can imagine, an analytics program will have problems making sense of that. Instead, you should have individual fields for each relevant data point. Fortunately, adding these fields doesn’t have to be a manual process. So long as the you’ve been fairly consistent with how you’ve listed these details, there are ways to automatically parse this information and create new fields automatically.

Bad data leads to bad analytics, but good data leads to great analytics. Get an understanding of how data moves through your systems, and how it might move better, and you can supercharge your analytics efforts. 

The keys to your company’s growth are in the data that accumulates every day. It’s there right now, waiting to be discovered. iCharts can help you find and make the best use of it, but only if you’re ready. Take these steps to make sure you’re prepared for business intelligence. To learn more, watch our “Preparing Netsuite for Business Intelligence” Webinar.