Did you know that your country’s lockdown restrictions were probably determined by the analysis of Covid-19 infection rate data?
The power of data in making actionable insights is irrefutable, but this event has highlighted the need for timeliness and precision in the data used.
Few will forget the shortages in grocery stores during March and April. Online shopping was also impacted as Amazon’s delivery times extended well beyond the usual “next day.” Sudden changes to demand and supply were to blame. But within a few weeks, shortages were almost gone and Amazon seemed to be delivering much faster.
Given the circumstances, these fast responses were astonishing, and it is very likely that analysis of real-time data played a key part. McKinsey’s research verifies this: “In the early days of the crisis, many companies rushed to assemble a supply chain control tower—a cross-functional team reviewing real-time data to make decisions quickly.”
It’s amazing what can be done by leveraging data in this way – pilot programs have delivered big reductions in inventory, improved availability and reduced delivery times. Yet it does not always come easy – a survey by Harvard Business Review suggests only 22% of organizations feel confident translating data into actionable insights.
Why? It is not always clear. The reality is that both retailers and consumer goods companies have vast amounts of data, yet they struggle to attain actionable insights – perhaps because the data is siloed across systems and business functions.
The impact of these data silos on key operational areas is significant. Merchandising and supply chain decisions are suboptimal or lack the precision needed to drive efficiency and stay competitive. In the area of supply chain management, McKinsey refers to existing approaches as being a “burning platform” and recommends the adoption of a control tower approach.
Control tower approach
But what if you could move beyond this “burning platform” and eliminate data silos to create universal data accessibility? This requires putting data at the heart of the control tower with emphasis on timeliness, accuracy and ease of use. This way you can access and align data from across the extended supply chain, to provide rapid and reliable insight focused on key outcomes like improving availability, delivery time and reducing overall inventory.
Operationalizing data in this way offers the ability to create value, driving perspectives into businesses that deliver efficiency. Connecting and delivering real-time data in this way is a key step on the road towards the autonomous supply chain – capable delivering amazing benefits in terms of automation, proactive response and delivering efficiency improvements.
For the consumers, the impact could be that shortages and extended delivery times, the likes of which we saw earlier in the year, could be resolved much faster – or perhaps not be seen in the first place.
While this may sound like something out of science fiction, it may not be that far away. Two years ago Harvard Business Review* said: “It’s not hard to imagine a future in which automated processes, data governance, advanced analytics, sensors, robotics, artificial intelligence, and a continual learning loop will minimize the need for humans.”
*The title of the article? “The Death of Supply Chain Management.”