Using Big Data in Supply Chain Management
Where do supply chains need the most oversight? How can enhanced analytics maximize efficiency and help these areas operate more smoothly?
Big data applications in an asset-intensive industrial setting like a manufacturing plant or an oil refinery need no introductions. Business leaders in these sectors have long awaited the ability to monitor on-site equipment performance in all its granularity, measure it against historical data quickly, and aggregate unstructured gigabytes of data from disparate machinery into easily interpreted and configurable dashboards. Now that it’s readily available to them, the whole thing feels like a homecoming.
Yet, many organizations have been unreasonably reluctant to carry over big data analytics into supply chain management, arguably an area in every business particularly subject to an abundance of complexity. According to an Accenture study, although 97% of executives are aware of the benefits big data analytics bring to supply chains, only about 1 in 6 had such measures in place as of 2014.
Smarter supply chains cut costs for everyone involved, supplier and client alike, so long as partnerships develop and act on the right metrics. Where do supply chains need the most oversight? How can enhanced analytics maximize efficiency and help these areas operate more smoothly?
Use data to deploy supply chain vehicles safely and cost-effectively.
Fleet Management
Businesses concerned with fleet metrics tend to focus primarily on the KPIs directly related to spend, such as cost per mile, fuel efficiency, and even controlled vehicle re-marketing. However, there’s something to be said for stretching analytics viewpoints to include long-term value adds instead of “pinching pennies” in the short term.
Condition-based maintenance programs, for instance, typically utilize complex data sets to determine if and when vehicles need servicing. As businesses switch to “just-in-time” inventory management models, the importance of fleet availability increases, as does risk. A decommissioned truck or van not only places immediate revenue in jeopardy from a customer service perspective. It also usually requires expensive emergency repairs and may even compromise driver safety in certain circumstances. As such, supply chain and fleet management should coordinate on data-driven oversight to keep transportation operational throughout its life cycle.
Weather
When winter storm Juno froze New York in 2015, analysts estimated its economic toll would cost businesses between $500 million to $1 billion. A single storm can do a number on service and profitability, which is why any supply chain management strategy would be incomplete without weather forecasting.
“Businesses should use weather forecasting as a springboard for supplier or 3PL negotiations.”
That said, nothing is more predictably unpredictable than meteorological activity. Knowing a storm is on its way doesn’t really do much to prevent or preempt its impact to a substantial degree. Businesses should use weather forecasting as a springboard for supplier or 3PL negotiations. Business leaders should leverage data to inject flexibility into service contracts beneficial to both sides, absolving all parties of blame when weather is at its worst and hopefully securing carrier engagement/satisfaction in the process.
Decision-makers should also develop robust in-house policies for operators, drivers and warehouse crews diverse enough to accommodate any eventuality. That way, workers know exactly what is expected of them when different phenomena occur. Heavy rain? Drivers should execute safer, more defensive driving strategies on the road as defined by supervisors. Snowfall shuts down a major thoroughfare? Warehouse pickers should switch over to other value-add duties like cleaning or inventory management to avoid labor cost waste.
Demand Forecasting
This one is almost so obvious, it goes without saying – supply chain management hinges on customer demand, where it will be tomorrow and how quickly businesses can respond to it.
What might not be nearly as evident is the effect misaligned supply/demand relationship has on the business beyond supply management, in the form of surpluses, steep product or service markdowns, and inadequate customer service. Businesses shouldn’t merely turn their attentions to the metrics supporting best practices, but set notifications and alarm bells on KPIs that may forewarn them of potential supply chain mismanagement while it’s still able to be resolved.
