Data Transformation Before Digital Transformation

Anyone who has been in the high-tech world for any length of time is likely familiar with the term “garbage in—garbage out.” It is one of those absolute statements that transcends the potential promise of both existing and emerging technologies.

However, despite the statement’s veracity, we—either technology creators or users—have not fully recognized the power of data’s impact on our automation initiatives. If we had, we would not be contending with disappointing returns on our procurement technology investment. You simply have to look at the results of industry surveys regarding the dashed expectations of CPOs whose digital transformation initiatives have failed to deliver the expected results. 

However, and in the post-ERP era in which user-intuitive solutions can deliver results within weeks and days versus months and years, the problem is not with the technology.

If the issues are not with the technology, then what is the problem? 

The Missing Data Piece

According to the Deloitte 2021 survey, our profession is experiencing a significant transformation beyond the familiar tasks of cost savings. In this brave new world, data—or access to quality data—takes on even greater urgency.

We emphasize the term “access to quality data” for a reason. The issues we are facing regarding underutilized and unrealized returns from our procurement tech are not due to a lack of data. 

Overall, IDC reports that between 2016 and 2020, the amount of data has increased exponentially to reach 44ZB. 

Breaking it down to an enterprise-level, the “average company manages 162.9TB of data,” while the “average enterprise manages 347.56TB.” Even small businesses are data-loaded, having to deal with 47.81TB of data. 

Given the above, it would appear that while we are data-rich, we are intelligence poor as only 5% of all data is ever analyzed. It’s like reading the title of a book and then trying to tell someone what the whole book is about.

Something has to change in our approach to gathering and managing our data to extract actionable knowledge beyond a paltry 5%.

Creating a Data Culture

Albert Einstein once said, “we cannot solve our problems with the same thinking we used when we created them.”

When applied to the data problem referenced in the previous section, Einstein’s words should not only resonate but point us in a new direction regarding our views of data. In other words, it is not enough to acknowledge the importance of information in running our businesses; we must extend that awareness to implement effective data practices proactively. 

In this regard, a March 2020 Harvard Business Review article offers some much-needed advice for laying a solid data practice foundation, starting with creating a data-driven culture.

What is a data-driven culture—what form does it take?

The Data Governance Team

Organizations must create a data governance team involving procurement, IT, and finance stakeholders at a high level. The governance team requires a mandate that focuses on everything from standardizing how data is captured to how it is managed and disseminated. 

Once in place, the governance team must assess their current data pool to identify the priority extraction of immediately usable data. They must also simultaneously manage any new data input using the same standards for both, in essence converging old information with current information to get to the point of a collective data truth.

Finally, and this is key, creating a data culture is not a one-time event. It is an ongoing commitment to manage the organization’s data in the same way that the finance team oversees the company’s money. In short, money and data are both currencies and are equally important.