We live and work in a very data-driven world. We track everything from steps we take in a day, how many likes we get on a Facebook post, visits to the company website, etc., etc. etc. When it comes to business, we are using dashboards to manage metrics and KPIs all to help us make sense of the enormous quantity of information in hopes to turn that insight into actionable items that will improve our business and our customers’ experiences with us.
You’ll hear far less people making decisions based on hunches, guesses, or their gut, and instead making decisions based on data, analytics, and crunching of numbers. When it comes to meeting goals and KPIs, data is especially important and is vital to every organization. The right data and metrics can give us a read on the health of our product/service, help us identify strengths and weaknesses, track improvement over time, diagnose problems, etc.
But is access to all of this data really living up to the hype? Sometimes it seems that the cost of the data outweighs the benefits. Instead of providing useful insights, oftentimes the data contributes to information overload. Do we spend too much time analyzing and not enough time actually doing work and servicing our customers?
There has been a large focus on collecting all sorts of data, but not nearly enough effort in developing reliable metrics and models that can consistently link the data to company performance. Several years back, The Walt Disney Co. started a pilot program with their Magic bands – a wristband that allowed resort guests to unlock their hotel rooms, pay for meals, enter the theme parks and obtain passes to attractions and rides. Imagine the amount of data that Disney was able to collect. The insights that they’d be able to extract would be phenomenal. However, imagine the people analyzing all the data – they must accumulate billions of data points in a year!
Disney has the sophistication and resources to effectively use this data for their marketing and operations efforts, but we can’t all be Disney. So how do we handle all of the data and metrics generated from our technologies, ranging from sales metrics and social media metrics to market research and customer tracking data?
Here are the top 3 mistakes businesses make when compiling data:
- Complexity and Simplicity. Present the metrics in a simple and clear matter. Too much data and including non-essential metrics can make things confusing and ineffective. Determine the issues you want to solve and only include data relevant to those issues. Looking at every single metric possible will only cause more confusion and to be honest – stress and headaches. Start small.
- Create dashboards and visuals. If you have several KPI’s that are not related, consider creating several, separate dashboards that monitor different metrics related to your different KPI’s. Putting all your metrics on one dashboard can cause confusion, but you also shouldn’t create so many dashboards that managing them becomes a challenge. Use visuals and graphs when needed but they shouldn’t distract from the data. And use graphs that work best for the data. Pie charts are great to represent percentages of a whole, but not great for showing changes over time. Again, simpler is better. No one has the bandwidth to analyze pages upon pages of data to get to a simple answer.
- Share the data. It’s important to share the metrics with those who are involved in specific KPI’s or goals. This will allow them to track changes and see how they can do their job more efficiently. If you are tracking on time delivery, but not sharing the on-time delivery report with your production department, then they don’t know what they don’t know! Sharing is key.
So how much data is too much data? There’s no definite answer, but there is a way to set yourself up for success following these simple steps.
- Stay focused. Set your strategic goals and set up the data collection and analysis around those goals. Having tons of data is cool, but if you don’t have a clear path on how it can help or what you are looking at, it can be a huge rabbit hole.
- Measure what matters. Just because some data is easy to pull, doesn’t mean it’s worth measuring. Hone in on the metrics that actual help solve problems and meet goals.
- Set baselines and benchmarks. While it might be great to know what the product sales are for a specific product in October, you don’t know if those metrics are good or bad. If you want to launch a promotion for specific products, you should know what the baseline performance is first to know if your promotion is working and achieves the goal or benchmark that you set.
- Historical data matters. Yes, you always want to look at recent data, but successful organizations maintain a library of baseline, benchmark and outcome metrics to improve service. They can learn how to optimally design their activities moving forward.
There’s no rule of thumb or gold standard when it comes to determining which metrics you should be reviewing. Each company is unique in their goals and objectives, but it’s important to remember that too much data can cause information paralysis. When you don’t know how to use the data, or you spend too much time just looking at data without creating a plan, it can prevent your business from reaching goals and achieving KPIs. Track the data that makes sense and save the rest for another time.
Senior Vice President, Commercial Lender