Data-Driven Decision Making and How to Get There

By Biju Kewalram, Chief Digital Officer, Agility GIL

Accurate data and effective supply chain technology are more critical now than ever before. Data-driven decision making is enabling organizations to flex their supply chains to cope with rapid fluctuations in supply, demand and transportation. And as companies and countries attempt to “build back better” from the crisis, lowering carbon emissions has risen up the agenda, and smarter supply chains are an important lever.

Ten years ago, this simply wouldn’t have been possible. Over the last decade, a number of technologies have emerged, with the combined potential to revolutionize the way we move products around the globe. 

We’re now moving into the stage of validation and implementation – accelerated by the current crisis – when the whole industry must push past R&D and into the industrial execution of smart systems. This stage will be critical in terms of bringing about actual, sustainable change.

What could the industrialization of these technologies mean for both businesses and consumers, and how can the businesses that haven’t yet implemented them catch up? 

The four key technologies driving change in the supply chain are blockchain, the internet of things (IoT), robotic process automation (RPA) and data science (BIRD). 

Blockchain generates data trust by enabling all players in a network to share a single (encrypted) database. Anyone with access can track the status and location of a shipment and, more importantly, identify opportunities for efficiencies on a larger scale than has been previously possible.

IoT technology is essential for gathering a vast number of data points. By implementing a system of smart sensors, stakeholders can accurately track sensory data (e.g., location, moisture, temperature, shock), reliably calculating arrival times and proactively responding to disrupted shipments.

RPA improves data accuracy in the chain by substituting human input (and resulting error potential) with software robots that update data within applications by reading them from other applications. This closes the “data confidence gap” when a chain of data updates is required (as in supply chains) to complete the visibility picture.

Data science is the key to unlocking this collective data value and making smarter decisions. Advanced machine learning is continuing to evolve, and AI will one day be used at each stage of the supply chain, although we are some way off this yet. In the meantime, setting up shared databases and making common inferences should be the focus.

What Are The Next Steps?

Now is the time to think about how these technologies can be transformed into deliverable solutions.We’ve spent a long time researching these revolutionary technologies, but only by starting to incorporate them into existing processes can we unlock their full potential.

Organizations at the front of the curve have been analyzing how these exciting digital solutions fit into their businesses, and at our company, we’ve supported a few pilots of certain technologies with clients who are eager to move their companies forward. 

So what are the key considerations when piloting new technologies?

Start Small

With a number of technologies waiting to be tested, companies must take an agile, experimental approach. Rather than endeavoring to carry out large-scale trials across the whole organization, businesses should start by implementing the technology in a specific part of the process and gradually scale it up. Working in this way will allow trials to be integrated into day-to-day operations, quickly and effectively gathering firsthand data on multiple technologies.

Consider Your Team

Selecting the right team is vital to running a successful pilot. Ideally, you want a mix of experts who can provide insight on how the technology can be applied to a specific part of the process and the impact this will have on wider business operations. They must also have the analytical skills needed to evaluate the findings and report back to stakeholders. Most importantly, they must be passionate about innovation. 

Partnering For Cocreation

Carrying out individual pilots is one thing, but companies must push the boundaries of cocreation to test these technologies on a larger scale. Any change to the process will have knock-on effects along the supply chain, and the success of many technologies will depend on strong communication. Running pilots with trusted partners of different sizes will allow companies to analyze the adaptability of new technologies. Partners will need to start by agreeing on the problem they are trying to solve and the method they are going to use, as well as how they will measure success and share findings. 

Our company’s partnership with electrified trucking company Hyliion is an example of how companies can collaborate to create a more efficient, greener supply chain. We’re helping the company with its long-haul, fully electric powertrain — the HyperTruck ERX. It can achieve a net-negative greenhouse gas emissions footprint using renewable natural gas, and the system’s machine learning algorithm further optimizes energy efficiency, emissions, performance and predictive maintenance schedules.

Gauging Success

Before embarking on a pilot, companies must set out some clear performance indicators and decide on a system for recording results. New technology may show promise for a specific task, but can it be scaled up? What impact would it have on costs, revenue and customer satisfaction? Approaching trials scientifically will help to determine the long-term value these technologies could have in terms of business performance.

Many pilots will inevitably encounter problems, but these experiences are still valuable. A comprehensive debriefing process is necessary to identify whether a failure was due to a weakness in the product or the process and whether these problems could be ironed out through further testing.

Of course, with the logistics industry evolving rapidly, there is no fixed end to the experimentation process. Companies that adopt this systematic approach with an analytical eye and a resilient attitude will thrive in the big data revolution. Organizations must be willing to disrupt their current processes and collaborate because partnerships will be crucial for implementing new technology and making digital supply chain dreams a reality.

This blog first appeared in Forbes