Big data and data analytics are two of the hottest topics out there today. They come with promises of delivering business insights and high returns, but they also come with challenges for those new to the field. As a consultant in analytics, the most popular comment I receive from companies is, “we have so much data but we don’t know what we should be analyzing.” This article will provide business leaders with several tips on where to apply data analytics in order to impact the bottom line. The key thing to remember is that the value of analytics is not in the data. It’s in what you do with that data to make better business decisions or solve business challenges.

Those that operate in the learning space are familiar with The Kirkpatrick Model® for measuring training effectiveness. This article will outline a simple method for evaluating online and on-site workshops. 

You purchased high levels of inventory to cover long lead times of overseas shipments and to leverage quantity discounts… and then it happened.

Taking the time to assess supplier performance is crucial since suppliers can make or break your business. Supplier reliability and flexibility have become performance factors that are just as important as price in order to protect your business reputation and top line. Setting up a method to monitor key supplier performance factors and studying demand patterns can help provide insight into supplier issues and set up a good path for reducing risk of the supply base on your company.

When You Just Can't Win: In HR Analytics, it is important to look ahead and think about unintended consequences. With some people analytics studies, you need to know when you just can't win otherwise you'll waste valuable budget/resources to produce no results. I'll provide examples.

Why is product rationalization important? As the number of products increases and products move through their life cycles, the percentage of products that become low volume and/or low profit increases. So how does product rationalization work? 

In the analytics world, there are teams that are “stuck.” This article is to help those teams get “un-stuck.” Perhaps you headed down the path of analytics without a plan. Perhaps you had a plan but the ever-changing data privacy regulations halted that plan. It’s time to refocus so you can begin to move forward once again.

The following overview is written as a guide to those new to analytics or new to solving business problems.

For those that attempt completion of workforce plans, the scenarios for these plans are almost always scenarios of growth. But the reality is, it is highly likely that a company will find itself in a reduction scenario at some point in time. It is these reduction scenarios where planning becomes crucial.

With all of our technology, big data storage choices, apps, data visualization tools and statistical packages, visibility and transparency remain a challenge for procurement teams. To make clear the difference between the two, when I speak of visibility, I am referencing the ability for procurement professionals to access and analyze their own internal procurement data. When I speak of transparency, I am referencing the exposure of procurement information to the public.

The concept of the Net Promoter Score (NPS) was first published in 2003 in an article called,  One Number You Need to Grow. It was created as a way to measure and manage customer loyalty without the complexity of traditional customer surveys. Since that time, the same concept has been applied in multiple functional areas to replace longer surveys that require too much of a participant’s time. 

Regardless of what you do each day, you’ve probably realized that you are surrounded by data. The quantity of data that exists in the world grows substantially with every passing hour and it is said that 95% of it has yet to be analyzed. That’s okay, because success in the data and metrics world is not about analyzing data for the sake of analyzing data. It’s about analyzing data to answer a question. There also has to be value in finding the answer to that question or you risk wasting valuable resources (time and money).

With gender and ethnic diversity being such sensitive topics in recent years, it is the responsibility of both Human Resources, Legal teams and math experts to proactively provide statistical back-up to certain workforce decisions. One important application of math to workforce decisions is in avoiding adverse impact.

Data breaches are in the news every day, especially the large-scale ones that occur at retailers and financial institutions. But did you know that most data breaches are the result of employees accidentally exposing sensitive data? These unintentional actions can have substantial consequences.

To solve your inventory challenges, you went ahead and purchased an inventory management system. The software vendor demonstrated great capabilities to you and you thought your problems were behind you.

You took the time to add all of your part numbers to the system, your list of suppliers and their contracted lead times. The inventory system went live, your employees were all trained in how to use it, but in the end, you’re still experiencing unexpected stock-outs, displeased customers and frustrated customer service reps. Clearly, your new inventory software doesn’t work, right?