The ROI Continuum: From Challenging Paradigms to a Long-Term Vision on Data Quality Excellence

Building upon the discourse initiated in our previous blog post regarding the challenging debate surrounding ROI measurement for Procurement Data Foundation initiatives, we now delve deeper into a natural consequence that emerges from this ongoing dialogue: the imperative of embracing data quality as a long-term initiative involving data stakeholders, especially the unconscious ones that are at the root cause of the current mess.

In Procurement, the initial data is rarely created by procurement people but mostly from other departments like engineering, supply chain, maintenance, and operations; many are seldom conscious of the data quality that Procurement needs to serve them properly and effectively. There is an entire market of Process Mining tools that can show how intricate and inefficient the whole process is due to one single fact: Data Quality.

Nevertheless, as a Procurement VP of an S&P 500 company stated: ""It is a struggle to upskill and cross-skill people, and also difficult to get investments from the board in that sense, even though they understand the value of data.”

This means that together with the existing data cleansing and harmonization delivered by AI-powered tools to achieve the “Get Clean” paradigm, an additional critical imperative emerges beyond. New data is encoded daily, so a “Stay Clean” technological paradigm must also be implemented to avoid returning to the starting point. It sounds obvious, but, in reality, many stakeholders, not all of whom belong to procurement, think “Get Clean” can be a one-shot activity. “Stay Clean” underscores the necessity of precisely maintaining data quality integrity over time because relying on human efforts is impossible.

Leveraging AI-powered solutions that can ubiquitously be integrated into existing software workflows for data creation becomes paramount in ensuring continuous data cleanliness, enhancing automation, reducing errors, and empowering informed decision-making across the organization.

By recognizing the intrinsic link between data cleanliness, cost avoidance, and productivity enhancement, the ROI justification for prioritizing data cleansing transcends financial metrics to encompass a holistic view of data as a strategic asset.