There’s a lot of buzz around data right now, what with the world cumulatively generating 2.5 quintillion bytes of it every day. With 90% of all data that currently exists created within just the last two years, these insights are coming at procurement departments at a breakneck pace, overwhelming the many connected devices, computers, and tablets they use on a daily basis.
This proliferation of data has pushed more organizations to think about how they can use the intelligence to improve performance instead of operating on gut instincts, historical knowledge, and narrow observations. By taking the guesswork out of decision-making, data helps create a more transparent procurement environment while also allowing buyers to make more informed decisions based on real facts (vs. assumptions or opinions).
How to Leverage Useable Data
Getting to the real, “useable” information that’s hidden within all of this data isn’t always easy, nor is figuring out how to apply it in the real world. “There are too many decisions made on gut feeling and anecdotes,” LLamasoft’s Toby Brzoznowski told Environmental Leader. “The more those decisions are replaced with a data-driven approach that allows new available analytics to take over, the more you can drive smarter decision-making.”
Here are five ways electronics buyers can break through these barriers and create a data-driven supply chain:
1. Start with clean, accurate data. Data is only useful if it’s accurate and relevant. According to a recent Experian survey, just 44% of organizations trust their data to make important business decisions while, on average, 33% of an organization’s data is perceived to be inaccurate by the C-level decision makers. “Therefore, data first needs to be refined and efficiently delivered for analytics to provide the desired value,” Alexander Blok writes in How to Use Data to Improve Supply Chain Operations, “which requires a versatile combination of integration and data management capabilities.”
2. Look at the points that drive true value across the organization. “Many CPOs and procurement teams are overwhelmed with the sheer volume, intensity, and diversity of data today, and struggle just to manage that data, let alone leverage it,” Corrina Owens points out in Big Data = Big Opportunity for Procurement. Within the strategic sourcing process, for example, buyers create or accumulate many different kinds of data at each stage (e.g., spend, sourcing, market/third-party intelligence, contract, supplier, procurement, and accounts payable/finance data). Within that context, the data can either be structured or unstructured, adding yet another layer of complexity to the situation. “If CPOs and their teams can overcome the management and analytic challenges of big data for procurement (i.e., by adopting automated solutions, and standardizing and linking their processes),” Owens writes, “then they will be well positioned to extract value from their data and drive that value across the enterprise.”
3. Incorporate all three aspects of supply chain management. Calling execution, planning, and design the three pillars of supply chain management, Brzoznowski says that execution asks, “How do I run my supply chain?” Planning asks, “How do I make that supply chain more efficient? Finally, design answers the question, “Is this even the right supply chain?” All three elements have to be in place in order to create a true data-driven procurement approach. “This is where data science comes in,” he tells Environmental Leader. “It can take all of the execution-level transactions and bring them together into a digital model.”
4. Don’t limit your data points. Too many procurement departments center on a few specific data points that their organizations have tracked for years, rather than unlocking the millions of data points that reside in the typical procurement process. The problem is that, regardless of whether these data points are being generated externally or internally, most of this data remains “inaccessible and unused because procurement teams struggle with how to turn it into the actionable insights they need,” Accenture Using predictive models that analyze requisitions, identify the correct buying channel, and predict the supply base and fair market value, for example, helps buyers make good preferred supplier selections and leverage contract pricing. By inserting analytics upstream in the buying process, Accenture concludes, procurement can effectively prevent savings leakage, minimize supply chain risk, and improve compliance.
5. Focus on turning the data into real business value. As data continues to proliferate at an unprecedented rate, collecting, storing, analyzing, and distributing that information has become easier thanks to technology. However, even this “curated” data is useless unless it’s been made actionable. Put simply, the best and most reliable data points and metrics are meaningless unless they are somehow leveraged in decision-making. “To address this challenge, data and analytics leaders need to address the perceptions of data quality,” Blok writes, “deliver tangible value, and communicate it consistently to business decision makers.”