How Far Will You Go for Data?

Accessing and utilizing data efficiently in a professional setting can be challenging, especially compared to the simplicity of obtaining information in one’s personal life. For instance, a food manufacturer needed help accessing data for purchasing decisions. Initially, the company relied on manual processes but later learned how integrating its IoT platform, MES, and ERP could provide buyers real-time data, improve productivity, and reduce errors. 

It’s only Monday night and your kindergartener is already looking forward to the weekend. They want to know if it will snow at all this week so they can go sledding on Saturday morning. That’s easy – you pull out your cell phone and check your weather app. But if your phone was dead, would you boot up a laptop? And if your Wi-Fi was out, would you check the Sunday paper? Well, it’s 2024 and you cancelled your newspaper subscription years ago. Would you go to a newsstand to get one? Would you call your local TV station and ask to speak to the weatherman? At some point you’ll determine this is more trouble than it’s worth, so you’ll give up and tell them they’ll just have to wait and see.

Unfortunately, your factory might be closer to the “wait and see” or “call the weatherman” side of the capability spectrum than the “weather app on your smartphone” side. Locating data at work can often be challenging as it may be spread across different systems, be difficult to identify, or sometimes users may need to be made aware of its existence. As we dig deeper into the world of data and its many forms, we will show how a manufacturing company dealt with this issue and how you can follow similar tips to bring your data closer to your users.

Users walk 500 miles…and then they walk 500 more

While leading a discovery project on potential Smart Factory initiatives for a food manufacturer, I visited a plant that found themselves frequently running out of a few key raw ingredients held in storage silos. The facility could hold up to a few days of safety stock due to limited storage. Because the facility ran 24/7 with vast swings in productivity, they needed purchasing to be constantly aware of current inventory, future production, and future deliveries. Imagine trying to plan every stop to the gas station without knowing how full your tank was or how far you needed the drive the next few days!

While touring their production lines, engineering touted the investments they had made, networking their operational technology and collecting data. They demonstrated how current and historical inventory levels for the silos were collected via load cells, were displayed on HMIs for operators, and were available to plant management remotely. When we asked engineering if that real-time information was available to the plant buyer, they answered “yes” – which might have been technically true – but a conversation with the plant buyer revealed they were unaware of the Smart Factory tools used at the plant. Plant buyers were working remotely during the height of the pandemic, and they relied on local operators to walk the floor and take pictures of the silo readings and send them via email. This took operators away from their lines and often resulted in errors when pictures got sent out of order. It also took the buyer time to open each image and manually transpose the readings.

Management was impressed by the buyer’s dedication to using up-to-date data to inform their decision-making but was astounded at how hard they were working to get data that could be made available in a much better way. 

Halfway There and Living On a Prayer

After we engaged with management to scope out a quick sprint and secure some resource hours, engineering and IT were able to quickly collaborate to get the buyer access to the plant’s IoT platform and create a dashboard specifically showing real-time inventory levels. The buyer was thrilled! The new process also had a positive impact on the shop floor – operators who used to spend 20 minutes each shift sending updates to the buyer were now able to stay on their lines and focus on their actual jobs. Yes, the buyer had to log into a new system, but the process to cut a purchase order in their ERP had been simplified; now they could plug in the values from the dashboard into their “re-order spreadsheets” at any time without having to wait for an operator to walk the floor.

Wait – spreadsheets?

Like most companies with ERP software, purchasing was using an MRP process that incorporates inventory, usage, and delivery data to determine the exact date material is required. So why did they have to use spreadsheets to calculate requested delivery dates? It turned out that they had to go out to multiple sources to get the information they needed; they had a new and shiny dashboard for inventory levels, a spreadsheet stored on SharePoint filled out by operators indicating day-over-day progress on long production orders, and an email inbox for ever-changing delivery dates sent by suppliers. So “yes,” all the data required to do their job was “available,” but in disparate locations and not readily visible to them at the place and time it would be most actionable. The buyer admitted that sometimes they placed orders without checking for changes in the production rates because the information took too long to compile. Putting data in hard-to-access locations can discourage its use – how much less often would you check your car’s fuel levels if the gauge was located on the undercarriage? Engineering and IT had only solved part of the problem, and they had only solved that part partway!

Everything in Its Right Place

Now, imagine the story picks up months later during a digital transformation. The company had secured resources and investments to create sustainable practices that would let them scale more efficiently. At this point, they had a local buyer (or two, or three!) for each plant. Leadership wanted to find ways to leverage technology to add production lines and even plants without adding headcount to the purchasing organization. And by now, they knew the answer was to bring the data to the user in real-time, when they need it, where they need it, and eliminate time collecting and consolidating. They also wanted their digital solutions to enable remote work so buyers could cover multiple geographies.

So, where does purchasing need data? Purchasing lives and dies in MRP (in ERP) – where the data belongs. The company decided to interface data from their IoT platforms and MES to their ERP, where buyers can access production order progress and inventory in real time. They also chose to implement a supplier collaboration tool, where vendors can update delivery dates, which will feed right back into their ERP (in addition to having access to updated forecasts and specification data). Finally, buyers will have one system with all the relevant, up-to-date information they need to place orders readily visible – and it is the same system they need to go to place orders in the first place. They also discussed setting up alert parameters in their IoT platform so they can be notified on their mobile devices if a change to the production schedule, higher than normal scrap, or unexpected downtime will require them to urgently adjust a delivery date. The goal is to make each buyer more productive and less error-prone, letting them cover more materials and spend less time firefighting.

How You Can Go the Extra Mile So Your Users Don’t Have to

So, how can your company make data work for users instead of having users work for their data? Here are a few things to consider as you implement data collection and visualization tools.

Take A Process-Focused Approach

When launching or re-launching any project involving data, let your PEOPLE and your PROCESS drive your data strategy, not the other way around. This might sound obvious, but it is still common to see companies build dashboards based on the data they HAVE and not the data users NEED. With a data-centric approach, you risk having data in the wrong system (because it was convenient) or being inaccessible to key users (because it is in the wrong system or they don’t know it exists). You will achieve better adoption with a user-centric approach that starts a strong understanding of what information users already consume, what additional information they need, and how long they spend collecting and analyzing data themselves. That will help you prioritize your efforts, attack the most impactful or profitable use cases, and make sure your data adds value. Have workshops with a few users from each department to walk through their process and ask targeted questions about their data behaviors and needs; it is guaranteed to be time well spent.

Be pushy

No matter how hard you have worked to have an integrated technology landscape, it is pretty likely your users are logging in and interacting with several different systems each day. And the more places they have to go to get data from, the less likely they are to go and get it. So now that you have taken a process-focused approach, and you know WHEN your users need data and HOW they are going to use it, PUSH the data to them at their point of use. You can do this by displaying it on monitors on the shop floor, sending them mobile alerts, and integrating data into the systems they already are comfortable interacting with. You will also avoid situations where users are unaware of the data available – because it will be right in front of their face!

Socialize – and I don’t mean at happy hour

Building a data-driven culture means changing how people think about and use data. And for the data you cannot push to your users, like ad-hoc reports or sensitive information, you have to educate users on the data’s existence and location. As you launch new tools or make new data available, it is critical you have the right change management programs to communicate the availability of these tools, build trust in the data, and DRIVE adoption. Or even better – involve them in the end-to-end implementation process, from gathering requirements to data design, testing, and training.

To SUSTAIN adoption:

1. Nominate data ambassadors within each department to be super users of the tools and use cases relevant to their teams.
2. Use formal documentation programs describing how data is collected and manipulated before being served to users.
3. Hold roadshows with your users to continue the discussion and collect new use cases or data needs on an ongoing basis.

Where to go from here?

If your organization needs to utilize data to its fullest potential, it may be time to reconsider your data collection and presentation methods. InSource Solutions is available to assist you. Reach out to us, and we will be happy to explain how we can create a tailored plan for you to implement the right tools and strategy to improve your organization’s data-driven decision-making.