by 
Alex Saric
Data is the main enabler of digital transformation and, by extension, of all the efficiencies that flow from it. In industry after industry, data-driven insights have, to a great extent, displaced more traditional approaches to business decision-making. As a result, accurate data has become an essential tool of digital management. Bad data leads to poor decisions. And that applies to an organization’s internal process operations as well as to its relationships with external customers, suppliers, and other stakeholders. But lately, circumstances have conspired to make the identification and collection of good data significantly more difficult.
Consider the outbreak of Covid-19. Before the pandemic, few people would have characterized the world of manufacturing as either static, predictable, or normal. It was, after all, a period of rapid change in technology, in consumer preferences, and distribution channels. But now, with the benefit of hindsight, it almost seems to have been an era of business as usual – a well-oiled machine for international commerce. Then the pandemic appeared and threw sand into its gears. In large measure that happened because, as the ripple effects of the infection made clear, there were many factors impacting production, distribution, and marketing that had never been seriously taken into account before.
For example, there was the slowdown or even shutdown of otherwise reliable suppliers whose workforce had become sick. Or the abrupt shift in consumer demand toward durable goods, the shortage of truck drivers, the lengthy delays in unloading ships arriving at U.S. ports, the shortage of shipping containers, the slowdown in customs clearances, inspections, and other administrative functions due to high absentee rates. How do you track all of that? And how do you analyze it?
The combined effects of component shortages, layoffs, clogged ports, and absent workers were then exacerbated by other, non-pandemic issues, including anomalies such as severe weather impacting petrochemical production in Texas, or the Ever Given container ship grounding and blocking the Suez Canal. These developments had direct effects on certain industries. But their indirect effects on secondary and tertiary links in the supply chains of many others impacted a far greater number of organizations.
In an increasingly interconnected world, where distant events with no obvious connection to your own affairs can ripple through the global economy, it is not practical, or even possible, to account for every contingency that can affect your business. That’s why purposely maintaining operational agility is a strategy for survival that applies to virtually every type of business. Working with a combination of your own business process data and information from established suppliers, augmented by third-party sources, can make options visible that might otherwise remain hidden.
If there was anything good that came from the pandemic, it was that the disarray it prompted prioritized a recognition among business leaders of the need for accurate data to solve short- and long-term supply chain challenges. It was, for most companies, a wake-up call emphasizing the importance of getting their data houses in order. In the early stages of Covid-19, where the problem was believed to be centered in the Chinese industrial city of Wuhan, companies rushed to assess their exposure to businesses based there, and indeed they found some. But there were far more instances of operational issues stemming from Covid exposure among their second and third-tier suppliers – vendors about whom little was known.
So where do you start on a journey of digital transformation to overcome these data gaps? First, take a look at the data you already have. A lot of it resides in your organization’s backend systems. There, you may recognize opportunities to integrate master data management – where business and information technologies are combined to enhance uniformity, accuracy, consistency, and accountability of enterprise data assets – with spend-management software suites
Then ask how you can partner with your suppliers to augment and take advantage of that data. Reaching those key suppliers, accurately assessing everyone’s essential inventory and exposure, and making the resulting data available to your stakeholders, is critical for realistic supply chain forecasting. However, that requires making involvement as easy as possible for those suppliers – removing any burdensome fees or conditions – to supercharge adoption.
Finally, consider data accessibility. Users should be able to access important information wherever they happen to be along the process – something that many companies undergoing digital transformations fail to recognize or implement.
Establishing a single record that includes your internally generated data and information from third-party sources, along with your own spending and work processes, isn’t easy. But technology packages from different vendors can help you mobilize and deploy sourcing and contract management in just weeks, with significant ROI within months. Later, as the system matures, maintaining flexibility becomes a central issue, as the pandemic vividly reminds us. Maintaining versatility is a huge advantage when requirements change, the market changes, your mix of suppliers’ changes, or your development team comes up with new concepts.
Although it’s not possible to know in advance everything that can impact your business, a company that has transformed itself into a data-driven organization using a sound technology platform can more quickly adapt to fast-changing conditions, create sustainable value, strengthen continuity, and establish transparency. And all of it begins with good data.
