If your CEO or CIO were to ask you how you are helping your organization use data to your advantage, what would you say?

Would you have an answer when it comes to categories of spend like transportation or indirect goods? Questions such as these are likely to send you running to research new tools to help.  

When addressing the challenge of putting your data to work, the first question is: Are you saving all your data? There are billions of procurement transactions annually — an estimated 10,000 shipping containers are lost at sea each year — so it’s no surprise that collecting, saving and organizing procurement data is a challenge. If you’re struggling to save your data in an effective manner, you’re not alone. Fortunately, data is becoming digitized, and as we see more and more articles claiming that “data is the new oil,” a slew of new tools to save and organize it is on the way as well.

The effective use of big data effectively can reap substantial benefits. The success of real-life applications in transportation, sourcing and procurement validate the time and effort. For example, the city of Brisbane, Australia was able to reduce traffic congestion by leveraging data points and making a few changes to the grid. UPS stores 16 petabytes of data to help make decisions, handling more than 39.5 million tracking requests a day from customers. As a result, it has managed to stay competitive against Amazon.

So where do you start? First came business intelligence (B.I.) tools, followed by spin-offs in each category being rebranded as artificial intelligence. However, few of these A.I. and machine learning tech companies have been able to make a dent in the problem, due to a lack of organized data. Step one in the journey is the need to retain data.

Humans are prone to centralization. It’s estimated that 68 percent of the world’s population will live in an urban area by 2025. Similarly, 65 percent of business teams prefer to work within centralized functions globally. While no one model works for all supply chains, centralized decision-making tends to reign supreme, with the largest companies outsourcing key functions to cut costs. The same can be argued for data governance and analytics. Having a centralized team that can work cross-functionally within the supply chain will better help your organization leverage the power of data and make better decisions

So what kind of data should be used to accomplish those goals? As Forrester reports, 74 percent of firms say they want to be “data-driven,” but only 29 percent are actually successful at connecting analytics to action. Do you remember the last 10 quotes your I.T. value-added reseller gave your organization for the same server? How about the last 150 freight spot quotes from your go-to third-party logistics provider? Organizations rarely save all of their data. But just because you went with another vendor doesn’t mean you should throw its pricing away. You should put that data to work.

Data strategist Brent Dykes argues that “actionable insights” are the apex of the data pyramid, which consists of six levels: alignment, context, relevance, specificity, novelty and clarity. It’s common knowledge that I.T. offers the best discounts in the fourth quarter, but how can you use data to predict behavior at other times of the year, or leverage the size of your organization to get a better price? Being able to identify positive business outcomes will help you achieve results, by narrowing your scope and aiming for a specific goal. Your flashy new rebranded B.I. tool can’t do that.

Personally, I’m saving my data. I have a plan, and now it’s time to reap the benefits. If you’re trying to maintain competitive advantage, put your data to work. A.I. today is really just extensive machine-learning models, or a combination of neural networks. Companies that succeed with their A.I. and M.L. technology partners are those that are looking to solve concrete objectives with large data sets. Are you going to be one of them?

Tarek Alaruri is co-founder of Fairmarkit.