The greater data ecosystem: driving decision making with AIBy Will Dutton on December 3, 2020
The phrase “data is the new oil” has found its way into just about every business presentation since it was first coined by Clive Humby back in 2006. The statement, although contestable (since not all data has the same ‘octane’ content), does beg the question that should always follow: what data?
As the COVID-19 pandemic continues to disrupt the majority of industries, its impact on supply chains has been nothing short of seismic. As teams face increasing pressure to make the right decisions at the right time, squeezing every last drop of insight and information out of your vast amounts of data has never been more important.
These tricky times call for a new approach to data-driven decision making, and there’s now a real need for supply chains to focus on, what we call, the greater data ecosystem.
Yes, you can make effective decisions based on data from your current systems, or by joining up a few previously-siloed sources across your organization – but there’s potential to go even further than this. The more data you have to play with, the more informed your supply chain decisions will be. Let’s take a closer look at a few different data sources that Peak is exploring with our customers to drive intelligent supply chain decisions.
Customer systems and D2C data
This is all about linking data from your own supply chain systems with your customers, as well as consumer behavior data points (for those with direct-to-consumer channels.) For instance, this could be their ERP system or even the logistics systems between your business and your customer.
For example, suppose you’re a consumer packaged goods business or a manufacturer, with a better handle on Electronic Point of Sale (EPOS) and any other sell-out data from your customers’ systems, you can better predict what demand is going to be like, and better understand their stock levels in order to help you anticipate yours. You could even factor into account things like receipts data; what baskets are shoppers generally buying together, and how can this help you better anticipate how groups of products are going to sell together.
This closer relationship with your customers’ systems allows you to better serve them and increase efficiency and anticipate demand fluctuations. In short, it’s all about creating more competitive supply chains which are more cost-effective, with better service levels and a more accurate view of demand.
By leveraging data points from your suppliers’ systems, you can plan ahead in the most efficient way and execute an effective just-in-time (JIT) inventory management strategy, holding minimal assets to save cash and space whilst still fulfilling customer demand. Our customers who are employing this methodology are able to understand when a supplier is going to deliver, to what location, and anticipate the arrival of goods and raw materials whilst also better understanding working capital implications.
Environmental and global data
Don’t underestimate the power hidden away in external, third-party data sources and the impact it can have on your supply chain decision making. Think about the ways your business can utilize, let’s say, macroeconomic data to understand what could be driving issues connected to supply and demand. Yes, we immediately think of things like GDP, or maybe even exchange rates, but there is now a plethora of data out there, that may be more industry and company-specific, that helps predict demand or implications for business performance. For instance, a sad but apposite data feed could be the level of COVID-19 near a supplier, which may hamper their ability to supply. Potentially, AI and machine learning could help understand the impact of these incidents with supply performance.
Network Data Sharing
If companies begin to institute data sharing in their supply chains at the same time, they will be in a much better position to deal with a future shock.
World Economic Forum
This one may seem a little more blue sky for many businesses at first, but the benefits can be enormous if you can imagine not just working closely with your retailers, but also with competitors and those providing similar products – allowing you to gain a unique view of exactly what is happening across the rest of the market. This leads to a better understanding of wider trends and the ability to make better smarter decisions. With a mutually beneficial relationship with the wider network, you can understand supply issues, and work with competitors or neutral parties to deliver better products and services to your customers creating a form of ‘coopetition.’
Introducing a new type of business system
Tapping into the greater data ecosystem and utilizing it in your decision making offers an untold number of benefits for supply chain teams. However, to truly unlock this potential, a new approach – and a modern architecture – is needed.
In the same way that business functions have their own systems of record, the ability to power decision making based on a wide range of data sources hinges on the introduction of a new, centralised enterprise business system. For Peak, this is CODI, our Decision Intelligence system, which gives teams the ability to leverage unlimited data points at scale and speed.
With CODI, we’re able to connect the dots between data points with AI, to prescribe recommendations and actions to help you optimize your decision making across the entire supply chain.
For instance, by feeding external data into both demand and supply planning systems and leveraging it with AI, you can optimize that connection between these two core areas of your business. Not only does it allow you to better sense demand with a higher degree of accuracy, but also enables a better understanding of how supplier and operations constraints are affecting supply – automatically making micro-adjustments to optimise the way demand is being fulfilled.
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...to find out more about the impact of decision making with AI, and the potential access to the greater data ecosystem carries for your supply chain.