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Building An A.I. Powered Negotiation and Procurement Chain, with Kevin Frechette and Tarek Alaruri Ep #106

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Procurement chains become increasingly complex the larger an organization becomes, which means that many gaps occur that cost the organization money rather than saving it. Valuable, cost-saving data is missed or lost, processes are elongated, and inefficiencies grow. A.I. and Machine Learning are tools that can be used to address these issues and many others. It’s up to us as the procurement professionals in our organizations to open our minds to the possibilities, learn about what’s happening with A.I. and M.L. now, and begin to integrate what we learn into our current procurement chains for the benefit of our organizations, teams, and customers. Join me as I speak with Kevin Frechette and Tarek Alaruri of Fairmarkit, a company that is using these tools to automate buying decisions, achieving cost savings of over 15% on non-strategic spend.

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Outline of This Episode

  • [0:35] An introduction to an amazing machine learning company
  • [4:47] How companies can begin to leverage automation
  • [8:14] The biggest gaps in negotiation that machine learning and A.I. can help with
  • [13:53] How human beings can learn from the AI tools being developed
  • [17:04] What areas of automation have not yet delivered on their potential?
  • [19:54] Where Tarek and Kevin see M.L. and procurement going in the next few years
  • [23:15] Why a lack of the right people is slowing down the vision for M.L. integration

What does machine learning provide to the procurement chains?

“Tail spend” is a term that refers to the non-strategic, non-complex spend that accounts for a relatively small percentage of a company’s overall spend—but also accounts for a disproportionately large percentage of its total transaction volume and vendor base. It’s often seen as a lesser priority when compared to strategic initiatives, but the cost-savings that can be realized through increased efficiencies in these areas can provide much-needed revenue that can drive those primary initiatives forward.

The solution for many companies could be automation through the use of machine learning and A.I. Companies like Fairmarkit are proving that efficiencies that come from A.I.-driven automation can make huge contributions to the procurement chains by analyzing activities that are repeated and that include lots of data, and by then making recommendations about better approaches.

How can machine learning and A.I. help large organizations?

We often find that the datasets collected and used by individual departments in larger organizations are not well-integrated and thereby cannot be used effectively for the organization’s benefit. But that’s just the first step in addressing a still larger problem. Once the data is brought together, what do you do with it? How will you glean insight from it? How will you determine what it means and what actions should be taken as a result? That’s where machine learning and A.I. come in. These smart technologies shine when it comes to combining and analyzing datasets. In many cases, these tools can not only review the data, but they can also initiate actions as well.

What would happen if human error and bias were removed from the negotiation process?

There are numerous points in every negotiation where perceptions are in error. Other times, facts are misunderstood. These are very natural, very human aspects of the negotiation process. But what could be possible if we find ways to remove those mistakes or missteps from the process? What types of gains might we see? Some A.I. based tools already in use observe human facial expression to evaluate emotion and responses, providing more data to understand what’s going on beneath the surface. Other tools are able to assess voice inflection and tone to build a database of observations that provide an ever-growing understanding of the people involved. All this technology, though unnerving to some, should be a welcome addition to the negotiator. They will only serve to help us do what we do with greater accuracy and excellence.

A.I. and Machine Learning will make the best negotiators even better

There will always be a place for skilled negotiators. The human component of every negotiation is never going to go away as long as people are involved in the process. And the skilled negotiators of the future will be the ones who use the available tools to their advantage. A.I. tools will help negotiators know how to phrase things and how to point the conversation in constructive and beneficial directions. They will also be helped to avoid the human error and bias involved in every negotiation. The utilization of such a dispassionate, logical tool is nothing but a benefit, an asset for skilled negotiators. Then it’s up to them to infuse the negotiation with the wisdom that flows from the data and then integrate it alongside the emotional and relational wisdom they’ve gleaned from years of experience.

Resources & People Mentioned

Connect with Kevin Frechette and Tarek Alaruri

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