Using the greater data ecosystem to drive great decision making

The phrase ‘data is the new oil’ has framed a large amount of discourse in the twenty-first century. The statement, although contestable, does beg the question that should always follow: exactly what data are we talking about? These tricky times call for a new approach to data-driven decision making. There’s now a real need for supply chains to focus on the greater data ecosystem, accessing wider sources of data and utilising it to its fullest capacity. While making effective decisions based on data from current systems, or by joining up a few previously-siloed sources across the organisation is becoming easier than ever – there’s potential to go even further than this. The more data there is to play with, the more informed supply chain decisions will be. Here are four data sources that can help accelerate smart supply chain decisions:

1. Linking the supply chain with customer systems

The more systems that talk to each other, the better. Linking data from supply chain systems with customer systems, including behaviour data points, can help understand the pain points that arise. For instance, this could be the customer's ERP system or even the logistics systems between the business and the customer. Taking consumer-packaged goods businesses and manufacturers as an example, with a better handle on Electronic Point of Sale (EPOS) and any other sell-out data from customers’ systems, the business can better predict what demand is going to be like, and better understand their stock levels in order to help anticipate their own. Factoring into account things like receipts data, what baskets are shoppers generally buying together, and how can this help better anticipate the groups of products that are going to sell together. This closer relationship with customers’ systems allows the business to better serve them, increasing efficiency and anticipating demand fluctuations. Inherently 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.

2. Supplier data for efficiency

By leveraging data points from suppliers’ systems, businesses 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. By employing this methodology, businesses 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 the working capital implications.

3. Using environmental data

Don’t underestimate the power hidden away in external, non-industry related data sources and the impact it can have on supply chain decision making. Think about the ways a business can utilise, 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. In recent months, appropriate data feeds impacting the supply chain could be an increase in Covid-19 cases near a supplier, hampering their ability to operate as normal. Connecting these data points up to technology such as Artificial Intelligence (AI) could help understand the impact of these incidents with supply performance, and create accurate forecasts on the trends.

4. Sharing data across the network with co-opetition

For many, the rule of thumb is not giving the game away to competitors, so this may seem a little pie-in-the-sky for many businesses at first. However, the benefits of sharing data with the industry and accessing competitor data sources can be enormous. The data of those providing similar products is at first harmless – but using it in the right way, to make intelligent decisions, will allow the business to gain a unique view of what is happening across the rest of the market. This ultimately leads to a better understanding of wider trends and the ability to make smarter decisions. With a mutually beneficial relationship with the wider network, a business can understand supply issues, and work with competitors or neutral parties to deliver better products and services to customers creating a form of ‘co-opetition.’

Accessing the ecosystem requires digital transformation

Tapping into the greater data ecosystem and utilising it in decision making will be essential for supply chain teams to run smooth operations in disruptive climates. However, to truly unlock the potential this offers, a central AI system 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 AI system. Using AI gives teams the ability to leverage unlimited data points at scale and speed. Utilising AI in this manner, to make decisions that are both smarter and faster to supercharge teams. At Peak, we call this Decision Intelligence (DI).

Decision Intelligence results in being able to connect the dots between data points with AI, to prescribe recommendations and actions to make more informed commercial decisions across the entire supply chain.

By feeding external data from the points above into both demand and supply planning systems, leveraging it with AI, enterprises can optimise that connection between these two core areas. Not only does it allow a better sense of 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.