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Data-driven supply chains remain a hot topic in the past few years, with pandemics, lockdowns, transport crises, container ships held outside ports, war in Ukraine and other issues wreaking havoc. The problems caused by these events are ongoing, but if addressed by a proactive approach rather than a reactive approach, there are ways to reduce their damaging impact, especially as the analysis and processes become apparent.
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“What we’re seeing with customers focusing on a data-driven supply chain is enabling data-driven decisions at all levels of the organization,” says Singleton. “Historically, supply chains have been slow to adopt technologies and analytics, but considerable progress has been made to upgrade systems to capture critical data in the supply chain. How to back and enable our people to make decisions – backed by that data – to create a proactive supply chain, a reactive one to market conditions.”
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Anticipating rather than responding to supply chain issues is also a major means of giving companies an advantage over their competitors, not only by being able to access increased amounts of data, but by being able to use that data effectively. instrument of. targeted way.
“Data in general has been exploding over the years in all aspects and in all verticals,” says Abel. “And in the area of supply chain in particular, given the challenges of pandemics, wars, chippedons and everything else, there is the potential to leverage that data and build transparency up and down your entire supply chain and run analytics on that.” . A game changer is happening now.”
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But when this kind of complex disruption, battles on multiple fronts, is when analytics and data become even more important as a blunt object to manage multiple crises at different points in the supply chain. Requires a more sophisticated, targeted and precise approach than running. The ultimate goal is to end the climate for the crisis before it happens in the first place, but the common denominator is talent and place the right people who are equipped to find answers.
“We focus on technology, which generally deals with database, BI and analytical solutions,” says Patel. “All those things are pretty mature and available, and many companies have implemented them over the years. So we have good technology available and we want to use it effectively. But when we look at the supply chain, a lot All the data falls apart, and collecting or connecting it in one place so you can do these in-depth analysis and visualizations across all those data sets is a difficult problem to solve. The people side of things is the hardest element. Many people are used to having reports, dashboards and basics and I think we need to increase the level of understanding of the data and then help the experts who can answer the tough questions.”
Abel, Patel and Singleton recently spoke with Ken Mingis, executive editor of Computerworld and host of the IDG Tech (Talk) podcast, about the organizational benefits gained through a data-driven supply chain, and how to get that data to the right people. able to explain. Informed decision.
Here are some edited excerpts from that conversation. For more details watch the full video below.
john abele
John Abel on data management: Supply chain planning has been around forever. I know my role. I’m used to the rearview-looking aspect. Some don’t know the art of the possible or the potential there, so it’s not that they don’t know what to do with it, but there isn’t anyone on their team who has the skill set to make the art of the possible.
So it’s bringing skill sets into the organization to make up for it. At the same time, most companies are lagging behind. This is going beyond the traditional view that supply chain professionals had to simply deliver results based on traditional KPIs. So going beyond that and combining the traditional supply chain for information with customer data or usage, or with customer experience, is when you begin to understand what plays into your ecosystem of delivering better results that drive top-line revenue. Or brings down the bottom-line cost.
They are the results, ultimately, that drive most organizations. One important thing to note is that if you haven’t started this journey yet, it’s important to start sooner rather than later. Just look at the available data and understand. Then arm yourself with the right talent to understand your ecosystem and how you get the right results.
Manesh Patel
Manesh Patel on handling expectations: Many companies had their supply chains managed in a standard capacity. If we think about MRP, the downstream communication for suppliers and vendors, it is a complex problem statement in the first place. And I think doing the day-to-day, week-to-week type of processes was tough in the first place and a lot of companies were focusing on that.
Then with the pandemic, we all started reacting and handling these exceptions, which is very hard to do because they are all different. And I think we’ve become more efficient at addressing those exceptions over the last three years. However we still have a long way to go. Understanding those exceptions has become very important and one thing we have realized is that it is not a one-time thing. Whether for war, climate or anything else, this is a reality of our future.
Eric Singleton
Eric Singleton on Data Literacy: A warehouse supervisor may have looked at a dock or floor before and said, “Okay, I’m doing well for the day.” But now they can see key metrics and concrete UPH or KPIs. But how do they act on that? Just having data is not enough. It’s teaching your people to think with a data mindset and really teaching them to articulate, interpret and analyze data with a meaningful impact. So there’s a lot of components to just integration, but then it’s also empowering people to use the information they have.
John Abel on data volumes: Data volumes are growing everywhere. The good news is that the technology side can handle it. We are able to process and select huge amounts of data but the reality is that people are getting overwhelmed. So how do you convert recent big explosions in data into value, and what are the analytics you use?
One use case is that we are helping a customer in the sports world by equipping stadiums with networking equipment to receive large amounts of data and give back analytics, which they then turn into greater value for their customers. can. Those who can see the upcoming versions, parse it down and turn it into value, have a unique skill set and are hard to come by. It’s really about taking massive amounts of data into your ecosystem and beyond your ecosystem, and figuring out what value you can get from using analytics.
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