Can Procurement Learn to Love Self-guided Buying?

Over the last couple of years, self-guided buying has gone from being anxiously dismissed by procurement teams as an impractical and even risky request, to a trend that is being embraced by stakeholders and distributed buyers for the access and autonomy it affords them.

 Leading procurement are now coming around to the idea that self-guided buying is not just possible, it is inevitable. And – if managed right – it can be a high-value opportunity for everyone involved. It is time to prepare for the technology, data, and process implications that must follow. Data quality is a particular concern, and it was one of the reasons procurement did not naturally gravitate towards self-guided buying in the first place.

 Although self-guided buying initiatives are working their way from pilot to mainstream, it is important to acknowledge that procurement was not wrong to have concerns about data quality. As more organizations implement self-guided buying, data quality and spend categorization issues are likely to arise without sufficient governance and technology support.

 Procurement teams at the start of a self-guided buying journey will need to explore and define:

 What spend is in scope?

Even leading proponents of self-guided buying would not suggest that all spend should be eligible for management via this channel. Organizations will have to draw their own scope lines, delineating the spend, suppliers, and categories that are considered appropriate for self-guided buying, looking at both risk and efficiency. This scope will be different by company and will likely change over time as self-guided buying is better understood by procurement and the distributed buyers who use it.

 Where will the information come from?

There is a certain level of supplier and/or item detail that will have to be available to avoid buyer frustration and prevent unnecessary or wrong purchases. Many self-guided buying programs leverage supplier-provided data. There is an especial advantage to this if the information is gathered through a platform or marketplace that allows suppliers to update multiple clients at once. A challenge that remains to be solved is how suppliers will reflect the contextualization of their offerings across customers, while still making them accessible using natural language search.

 What factors will motivate buyers?

Procurement has long worried about the tradeoffs between improving the buyer user experience through self-guided buying and their continued mandate to deliver cost savings. While the company (more specifically: procurement) may want to draw the line for self-guided buying in one place based on their objectives and priorities, distributed buyers have a very different set of objectives and priorities and would probably draw the line differently.

 Procurement’s ultimate goal for self-guided buying should be to optimize scope and governance, taking into consideration efficiency, agility, savings, buying demand, inventory management, and data quality. One of the best ways they can do this is to err on the side of more buyer freedom while protecting data quality through technology.

 AI-enabled categorization is ideal for this requirement, as it can resolve existing data issues and train the system logic at the same time, addressing short and long-term needs in parallel. Of course, this comes with some upfront investment as well.

 For self-guided buying to work on an enterprise level, categorization systems have to be trained on good data. Companies can start with their own data or others’ data, but they should be confident that the data is of good quality. This will position them for additional quality gains over time. Data quality has to be seen and felt from the top-down and the bottom-up so that everyone at all levels of the company is working with data that can be tied to that of their peers.

 Without data quality safeguards, the ROI of system investments and also procurement’s brand reputation are in jeopardy. Neither of those is worth trading for distributed buyer independence. There is no reason for data quality to fall below a 95% baseline; if anything, that level of categorization quality should improve.

 Procurement teams may not still be totally comfortable with the idea of self-guided buying, but they are not the only stakeholder or decision-maker involved. Once support for self-guided buying achieves a certain momentum, procurement’s role becomes ensuring they can meet that business need without sacrificing data quality or systems integration.