How can supply chain managers use data to improve efficiency in the supply chain?
By MMH Staff · February 26, 2019
Editor’s Note: The following column by Mark Hill, chief information officer of Washington Frank, is part of Modern’s Other Voices column. The series features ideas, opinions and insights from end-users, analysts, systems integrators and OEMs. Click here to learn about submitting a column for consideration.
Between today’s highly competitive market and rising consumer expectations, it’s crucial that supply chain managers run as tight a ship as possible. Sixty percent of online shoppers aged 18-34 now expect same-day delivery, putting enormous pressure on businesses and logistics teams to keep pace with evolving demand.
Luckily, thanks to advancing technology, there are a lot of ways a supply chain manager can boost efficiency and drive results—chief among them being advanced analytics. Data is the gold dust of the modern age. Businesses are fast realizing the value of data in optimizing their business, and are clamoring to get everything they can from the vast oceans of information they and their customers generate.
But hauling all this data to the surface isn’t enough on its own. Businesses need to be able to draw precious insights from the endless swathes of information they sit on, and turn those into practical, actionable strategies. That means implementing intelligent analytical tools and sophisticated algorithms that can transform raw data into a plan to streamline operations, improve accuracy, speed up delivery, cut overheads, and identify new opportunities.
How can supply chain managers use data?
When it comes to improving the productivity of your supply chain, knowledge is power. Being able to use the data you generate every day to your advantage throughout your operations will create a more efficient, agile operation.
From IoT data that helps you see what’s entering and leaving your warehouses in real time to customer profiles, social media data, and even the weather, harvesting information from multiple sources can help you move from analyzing what happened yesterday to predicting what will happen tomorrow. Let’s look at some key areas where great data analysis can produce a huge uptick in productivity.
Whether you want to achieve successful lean manufacturing, tighten your just-in-time accuracy, or improve self-service customer tracking, proper traceability is something all supply chains strive for. Improving traceability goes hand in hand with reducing risk too; among other things, traceability is essential to minimizing the impact of product recalls should the worst happen.
Data management is central to keeping track of your product throughout the chain, from farm to table. If data is properly recorded and accessible to every link in the chain, managers can touch base with their product at every stage, helping maximize efficiency, address problems quickly, and improve customer satisfaction.
How you collect and process data generated throughout your supply chain processes makes a big difference—investing in tech like smart and IoT-powered sensors can reveal the kind of information that you need to refine processes and boost productivity.
Blockchain is also beginning to realize its potential as a tool for traceability, and those willing to take a chance on a technology that isn’t overseen by any intermediary could see improvements to the integrity of their chain, and cut costs associated with the repeated verifications required throughout the shipment of goods.
Investment in big data analysis can also be a massive boon to your customer service. As well as furnishing businesses with the ability to track orders and deliveries more effectively, companies can use data to better understand their customers’ needs, and get ahead of demand to make your customers’ experiences as smooth as possible.
No one expects supply chains to run perfectly 100% of the time. But if you have more data at your fingertips and a clearer overview of your operations, then you can pass that transparency onto your customers, keeping them in the loop when things aren’t going to plan, and building trust.
All of this data, no matter how you generate or utilize it throughout your chain, can all be added to your company’s collective data lake. The bigger your lake, the more you’ll be able to make accurate, timely forecasts.
Being prepared is critical to effective supply chain management, and the more you know, the better prepared you can be. Smart business intelligence platforms are increasingly able to produce precise, actionable forecasts to help you manage inventory, minimize disruption, and plan for “what if” scenarios a year or even two years down the line. By examining data generated by past events, you can be proactive and take a strategic approach, instead of reacting to events as they happen.
Even if your company is one of the 56% that don’t have a big data plan yet, you’re probably passively enjoying the benefits. ERP systems are constantly being infused with newer, smarter technology to optimize and even automate supply chain processes. If you want to go even further, data scientists and business analysts can help process the data pooled in your digital business management platforms and create reports and tactics that will take your business to the next level.
Originally published on Modern Materials Handling