February 16, 2022

4 Common Mistakes Companies Make With Their Analytics Systems

Translating data into profit isn’t hard – with the right system in place. But as the old saying goes, where there are people, there are problems, and analytics systems are no exception. The hard truth: when your systems are poorly built, reporting inaccurately, or simply costing your team precious hours by requiring a heavy hand, your company’s bottom line takes a hit.

When we’re building analytics systems or consulting for a client, we often see the same mistakes crop up over and over again. So we thought we’d lay out a few right here. Take control of your data reports by scanning your systems for some of these mistakes – and consider implementing some of these fixes.

Mistake #1: The IT Department Holds All the Analytics Systems’ Keys

IT departments seem like natural depositories for all of your company’s data: techy people who are masters of your operating systems should, by default, hold the keys to your people analytics and financial numbers too, right?

Rhetorical question. Of course your company’s data should be protected and secure in password-protected operational systems, but that doesn’t mean access to this data needs to be owned and operated by IT. In fact, by introducing a middleman into the data reporting process, you strip the data from the departments who actually need it. HR should be able to quickly and efficiently dive into reports on employee absenteeism or exit interview feedback. Accounting needs to have current and past monetary data at its fingertips to create accurate comparative financial timelines. And each department needs to be able to report their findings to the C-suite, who should have access to it all.

The Fix: Begin training your employees to think with data in mind. Those employees that work in the data every day should be the ones building the analytics systems they need. Free up IT to focus on support issues while you build a system that everyone can access. The result: a frictionless pipeline of data everyone can use to efficiently do analytics whenever they need to.

Mistake #2: You’re Spending Too Much Time Building and Cleaning the Data Sets

…Which means you’re not spending enough time analyzing them. We’ve found that companies tend to spend just 20% of their time understanding their analytics; the rest of the time (a full 80%!) is wasted on cleaning data, building out dreaded weekly and monthly reports, making presentations and decks for stakeholders, and sorting through never-ending mounds of CSV files.

That wasted 80% should be spent understanding the data and using those insights to make strategic decisions. Just 20% of your time should be focused on the secretarial stuff, like running reports, applying formulas and updating visualizations.

The Fix: Time to create your company’s version of the holy grail of analytics: dashboards. Your analytics system should have an easily integrated dashboard that pulls data from multiple feeds (we love Power BI and Power Query for this). This means that all you need to do on that dreaded first day of your next analytics period is do nothing except navigate to a dashboard that automatically updates on its own.

Bonus tip: For those employees in your company that own these datasets, remember to instruct them to follow the 7 Golden Rules for Cleaning Your Data.

Mistake #3: You’re Keeping Your Analytics Siloed

Organizational alignment is key to a healthy, successful company, and that’s a truth that reaches as high as your company’s overarching vision and as low as your humble datasets. Your data is like your company’s vital signs: it signals how healthy each department is, and therefore predicts the survivability (and thriveability!) of your entire company. Just like you can’t make a good overall health decision without knowing your blood pressure, you can’t create predictive models without integrating all of your analytics in one place.

The Fix: Connect everything. Sure, maybe your accountants don’t need to know how your employee retention is… but your C-suite sure does. Build your analytics system with tools that can connect multiple datasets at once (Power BI does this well) so that when it comes to reporting time, you can create and send a dashboard to your leadership that shows how well the company is performing overall.

Mistake #4: You’re Not Using the Right Data Visuals

Don’t think data can lie? Think again. Graphs can look skewed. Pie charts can’t report losses. And even worse: there’s currently no data presentation standard out there. You’ve probably seen it yourself within your own company: different departments will present stats and data points in different formats. This might seem like a minor issue, but it’s actually crucial: data visualization is how you take all of the data you’ve gleaned and tell a story. Visualizations reveal strange patterns, clear areas of growth or loss, odd distributions or meaningful takeaways. These are the things that are useful to stakeholders. But not if the story is skewed – or if it’s outright fiction.

The Fix: Pick your visual standard, and stick to it. One of the most widely accepted data presentation frameworks is the SUCCESS method from the International Business Communication Standards (IBCS). IBCS suggests not only using honest graphics, but also sticking with consistent color schemes, shading methods, and graphic presentations.

Need more guidance on building and managing your company’s analytics systems? Want more advice on how to nail data visualization and accurate, efficient analytics reporting? We’ve helped clients work through common mistakes like these for years, and we can help. Please don’t hesitate to reach out to us today.