WIPP Data Blog

Raw data that is stuck inside a website, database, or an ERP system is as useless as a hammer sitting in your toolbox. Or a fully charged iPhone with the power off. Or a guitar hung on the wall. These are perfectly good objects, but have absolutely no utility until YOU do something with it.

In order for your organization to perform with optimal efficiency, your data needs to be transformed from a raw state into specific action items that you and your team can execute on. Unless action items are being drawn from your data, the data is like a journal. Sure, it’s nice to have. But if you don’t learn anything from it, then you’re doomed to repeat the same mistakes. My company WIPP data, measures the success of a dashboard by the subjective metric, time to decision. The longer it takes to make a decision on a dashboard, the worse that dashboard is.

Here are tangible steps that you can take to increase the amount of actions you take from your data.

Know the decisions that you want to make.

Unilever famously has come out to say that they are using their data for good. They want to create a more sustainable future and they’re using data accordingly. For them, the decisions they need to make are ways that they can decrease their carbon footprint. When I worked for Tesla, and managed a portfolio of inventory, the decisions my team needed to make were how many pieces to buy, and how urgent it was to purchase.

There are so many factors that go into the decision making process. But first you need to know what decisions you’re trying to make. Here are some questions you could ask yourself to get you on the right track. Are you trying to increase sales? Cutting costs? Decreasing your carbon footprint? Exploring and not looking for a specific thing? Calculating the same thing over and over?

Alternatively, if this was at a deeper operational level, you could ask yourself “What action does this warehouse operator need to take right now in this moment?” This could unlock a whole new level of efficiency. A system-calculated prioritization list could cut through the noise. But again, this is YOUR decision. You have to know what decisions you’re trying to make that align with your business objectives.

Figure out your Decision Drivers

As the phrase goes, the best way to eat an elephant is one bite at a time. I don’t really like that phrase because my dad loves elephants. Nevertheless, you cannot tackle everything all at once. The movie Everything Everywhere All at Once should not be your mantra. You can get way more accomplished by narrowing in on a very specific task and optimizing for that. If your goal is to be more environmentally, friendly, then a great place to start, is to calculate how much water and electricity or coolant your organization is consuming.

Let’s say that you’re trying to reduce your carbon footprint. Where does most of your footprint come from? If you don’t know, that’s the first place to start. COLLECT DATA. Sensors and IOT products are the ideal if your use case allows for that. After that, manual entry with barcode scanners is a great second place.

After you have your data collected, use a Pareto to decide where your biggest impact is coming from. Ideally, this entire process should be automated. You should always know at any given point what the biggest drivers were of whatever you’re trying to measure.

Root Cause & Create Tasks

Once you know exactly what you’re aiming for and what your top drivers are, it’s important to start creating tasks. For our purposes here, there fundamentally two types of tasks: Do we know what this is? If not, go figure it out. If we do know, go implement a solution.

I like to think of this stage as a regular meeting with key decision makers and leaders. You look at your Pareto to see what’s going on and you ask your team, “It looks like the electricity usage for our facility increased by 50% on Thursday evening. Does anybody know why?” If you don’t know why, you’d assign someone. If you do know why, there was a team there after hours and forgot to turn off the lights, then you could implement some sensors or create alerts if the lights are on.

Many “solution” tasks should be considered experiments. Because of that, you’re likely going to have a lot of failures. Some solutions just won’t work. But you won’t know that until you try.

Conclusion

It’s really important to remember that numbers and data in and of them selves are useless. Numbers don’t do anything. They are not autonomous beings. They are not making any changes in your business. However, visibility into those numbers, and a framework in which those numbers get acted upon, is incredibly powerful and will elevate your organization to new levels.