Companies have access to more data than ever before, but more data doesn’t automatically translate into more insights and business value. How do you go from data to business value? Why is data context important? How do you turn insights into action? Those are some of the key questions I discussed with Stephen Husk, Supply Chain Engineer at BluJay Solutions, during a recent episode of Talking Logistics.
Going beyond the jargon
When it comes to data, there is so much talk today about AI, machine learning, and predictive analytics that it’s easy to get lost in all the jargon. I began our discussion by asking Stephen what is the first thing people should consider when looking at turning data into value.
Stephen notes that these tools are just a means to an end. “The real goal is to get the right data to the right people at the right time within the right context so they can make the right decisions,” says Stephen. “Any company, regardless of their current data ecosystem, can start solving problems with that philosophy behind it. That may lead to AI or machine learning, but you don’t want to start with the tools.”
Data Context
Stephen mentioned data context as one of the “right” things to consider, so I asked him to explain what this means. He says, “It’s the setting for your data, it’s the network of connections your data exists in. Data without context is meaningless. For example, if I see my accessorial charges are decreasing, I might think I’m doing a good job. But if I look further to see that my base rates are increasing, it might mean my carriers are just baking in those charges within my base rates and I’m actually not doing anything meaningful to reduce assessorials.
“What we’re really excited about is considering data context across the network,” continues Stephen. “A great example is primary tender acceptance rate. Let’s say in 2018, I had 65% tender acceptance and I move the needle to 75% in 2019, exceeding my expectations. I can feel really good about that increase. However, if I compare it to the broader network, I realize that tender acceptance was 70% in 2018 and today it is 90%. By measuring myself against that market baseline, I realize that I could actually be performing worse than last year and could be more exposed if another tight capacity market comes. So without that broader network data context, you’re operating blindly.”
Actionable Intelligence
There is a lot of talk now about actionable intelligence, so I asked Stephen what that means. He defines it as simply meaningful data that can be used to make a change. Meaningful data comes from data governance and data quality. “You need resources and processes within your organization to manage the data and ensure its accuracy, or technology to help you with that. Otherwise, the data can be meaningless and even dangerous to your organization.”
Stephen goes on to say that you have to ask the right questions because metrics are always changing and you want to make sure you are focused on the right things. “Measuring the wrong metrics can be more harmful than having no data or inaccurate data. You have to focus on cost, service, and cost-to-serve, and you have to view them in balance. Define your key performance indicators and the levers that move those gauges, understand the context around them, and be agile in defining what success is, because it’s going to change.”
Turning intelligence into business value
Once you have data intelligence, how do you turn it into intelligent action and business value? Stephen defines this as the process by which you lead users to make the best decisions. He says once you’ve decided on the levers you want to move, find the person or people who are responsible for that lever and ask them what they are doing to move the lever in the direction you want. Supply them with all of the pertinent data you have developed and show them how they can use it to them make informed decisions. He says getting users to adopt and use the intelligence you’ve developed is the measure of success for this process.
Throughout our discussion, Stephen provided many great examples of how to turn data into business value. He also provided some advice on how to get started and how to differentiate the leaders from the laggards. So I encourage you to watch the full video for all the details. Then post a comment and share your own thoughts and experiences with turning data into business value.
