While this blog focuses primarily on topics related to Procurement & Contracts, I am taking the liberty of discussing some principles that apply to other areas as well.

I read the MIT article stating that over 95% of GenAI initiatives have failed with mixed emotions. Finally, a prestigious institution stated a fact known to those who of us who have worked in this area. Having driven significant digital transformations successfully, I can confidently assert that there really is no excuse for these failures. With the possible exception of integration, the primary technical & technological limitations – processing power, computational speed, storage, network connectivity and speed, analytical libraries – have been largely addressed. IMHO, there are two main reasons – other informed sources will give you between 5 and 7 – viz. data quality and user education/adoption. Address those early and the scales tilt dramatically in your favor.

With regard to GenAI, let us state some basic facts

• Agentic AI / GenAI work on relationships primarily within a textual content. Simply put, it identifies combinations of words to make sentences, paragraphs, posts & presentations. Thanks to the incredible underlying technologies, it builds layers upon layers of relationships and amazingly produces high quality content which appears to make sense. Note however that it is not trying to do a traditional optimization nor make a true business decision i.e. caveat lector applies to all recommendations.
• The content that GenAI generates is dependent upon the information that it is fed. As was seen with Grok, it generated some extremely antisemitic content since the corpus of information inadvertently included some very inappropriate content. On the flip side, the higher the quality of the corpus content, the better the recommendation.
• GenAI is not free. The more extensive the search, the more expensive it is. As information proliferates, the cost of tokenizing the content – a geeky way of saying searching for and incorporating content – will at least partially offset the efficiencies due to improvement in technologies.

Having said that, I am extremely optimistic of the value that can be realized through GenAI and Agentic AI. Both are extremely well suited for text heavy business functions such as Procurement & Contracts. Using a very rudimentary version of the AI agents (think primordial Agentic AI), my team was able to save over $1.5 Million per quarter and it took only 3 months to set up and to start generating the value. Just FYI, this number was validated by the CFO. I am certain that today’s initiatives will realize significantly larger benefits.

A couple of quick points to consider a possible approach for your GenAI / Agentic AI initiative:

• Focus on the problem not the technology – (This is surely a trope by now). Most initiatives focus solely on leveraging a single capability or technology. That is similar building a house with only vertical pillars. A holistic or complete solution may also incorporate ML/AI (the quantitative part of AI), visibility, optimization, etc.
• Address the aforementioned bottlenecks by:
  • Educating the end-users at the onset of the project … or earlier. Increasing the user involvement significantly improves user-adoption, a key factor for success.
  • Limit the data scope and focus on high quality data. As much as possible, focus on data relevant to your business objective. Adding additional data has diminishing returns and usually brings additional issues such as data quality.

While developing and deploying such solutions, I had some very pleasant surprises.

• Value realization is actually quite rapid. Bottom-line benefits show up in as soon a month. Set up KPIs to track the realized value.
• Data quality improves quickly. A virtuous cycle is created where data is used more when the data quality is high and the increased usage improves data quality.
• Business silos start to break and cross-functional collaboration increases significantly. A second virtuous cycle occurs when the high(er) quality data and information is used by other business functions which in turn drives improved analytics and data quality.
• The users directly improve the solution quality. An educated user has an intuitive idea of what “good” looks like and where the value lies. They take it upon themselves to suggest modifications and actively participate in issue resolutions.

Regardless of whether you are planning to start a GenAI / Agentic AI project or planning to pause one, I recommend an excellent (free) book about building AI agents by Sam Bhagwat. It gives you several ideas to incorporate into your own efforts. If you need any assistance, please do not hesitate to reach us – Naresh Rao or Chand Sooran. We would love to connect.

Measurement is a way to set strategic direction.

One problem with measurement is that we tend to concentrate on that which we can size up. If things are difficult to assess, we might ignore them, no matter how relevant they may be to the conversation.

When it comes to procurement, the conventional wisdom is to focus on a set of commonly prescribed performance indicators. Yet, as the economist Steven D. Levitt has written famously , “The conventional wisdom is often wrong.”

Let’s talk about what these tactical performance indicators are and the holes they create. Then, we can come up with a more strategic framework.

We can boil down the conventional wisdom on procurement evaluation to the following deemed critical metrics as seen here and here:

• Cost Savings: did the firm pay the lowest possible price for the solution, once they determined what they wanted to buy?
• Speed: how quickly does the organization execute a purchase from requisition to delivery?
• Performance: how reliably did suppliers execute?
• Compliance: did suppliers adhere to the terms of the contract?

Other supplementary aspects might include:

• Spend Composition: what percentage of spending did procurement direct?
• Performance against Budget: did spending come in under budget?
• Quality: how did the quality of the acquired goods and services affect the buying firm’s efficiency?

Presumably, the evaluation of these statistics is absolute, not relative.

It is difficult enough for the enterprise to collect this data about their own activities. The only way that they can benchmark their level of accomplishment is to rely upon a third-party consultant to compare their performance on these dimensions to others in the consultant’s ken.

This may or may not be reliable or appropriate.

The problem with some of these elements is they may conflate factors that procurement can control with things that they cannot. The experience of companies during the Pandemic lockdown should have made this clear.

For example, how do we evaluate the performance of the procurement department on the basis of cost savings in a year in which price volatility was extreme? Should we blame procurement for not being able to smooth out prices paid in an environment in which suppliers put their customers on allocation.

Why is speed a useful thing to measure? Isn’t there a tradeoff between speed and performance?Taking time to investigate markets and vendors may create the conditions for better pricing, improved supplier execution, or higher quality.

There is a dynamic interaction between these criteria that a simplistic “KPI” approach can fail to capture.

All of these are indirect ways to try to establish procurement’s marginal contribution to the overall success of the enterprise.

The problem is that procurement could be doing a great job along these lines even as they hurt the performance at the macro level.

For example, procurement could source very quickly from the cheapest supplier in China a widget that they need. They do well on speed, cost savings, and budget, even as they controlled all of this particular spend.

But, if the company cannot get any of these inputs delivered to the U.S. because of shipping disruptions, or even if shipping costs spike, do we say that procurement did a good job? What if the Chinese supplier turns out to ship widgets that have a high failure rate? Shouldn’t we look at the quality-adjusted cost savings? How many companies actually do this?

If procurement is going to be a strategic function, then the C-Suite and the Board need to evaluate it in terms of competitive advantage.

• Revenue: did procurement’s activities lead to an enhancement of revenue?
• Margin: did procurement’s activities lead to an increase in percentage margin, margin dollars, and/or both?
• Risk: did procurement lead to an identification and mitigation of enterprise risk?
• Collaboration: how do other departments and how do suppliers describe procurement’s ability to work together to advance the interests of the buying enterprise?

It can be difficult to quantify these things.

How do we compare what revenue would have been with procurement’s involvement from what it would have been otherwise? Or to do the same exercise for margin?

For example, procurement could increase revenue by feeding intelligence from suppliers to marketing and product groups as they develop new products that leads to a growth-enhancing refinement.

Or procurement could reduce the risk of the enterprise by developing collaborative, mutually beneficial relationships with long-term vendors that ensured priority allocations when suppliers became constrained.

Procurement could have contributed to higher margins by paying up slightly for inputs from a more reliable supplier with a lower realized waste of production resources.

Of course, the conventional metrics wouldn’t capture any of these scenarios.

How should you measure procurement performance? Perhaps the best way to measure procurement’s strategic performance is to do so qualitatively. 

Measuring qualitatively means that we hire a third party to survey other groups within and outside the enterprise in a manner that elicits their true sentiment about procurement indirectly.

One consequence of this approach is that it would force the procurement department to be more collaborative with those who would assess its abilities.

None of this is to suggest that companies should discontinue their tactical assessment of the conventional metrics.

EdgeworthBox is a platform for procurement. EdgeworthBox’s digital transformation offers both transaction efficiency improvements and strategic relationship-driven sourcing.

We bring tools from capital markets to improve the current approach to acquisition. Suppliers can onboard easily, meaning that buyers can solicit a broader array of potential vendors than if they just solicit those with whom they have antecedent relationships.

Buyers and suppliers can access market intelligence more easily with our “market tape.”

Finally, buyers and suppliers can communicate, frequently and across multiple functions, developing the foundations for trust, with our social network.

Whether you’re a procurement professional or a sale leader, we are looking for feedback on how to improve the process.

To learn more about how to optimize your outcomes, or share your insights, contact us.H

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