While our fearless leaders are forging ahead on a new way to think about quadrants / 2x2s / matrices / [insert consulting-term du jour here] to help procurement practitioners make better decisions in real time — more on that initiative very soon — we figured we’d point to a classic 2x2-style look that the World Economic Forum takes on global risk in 2017, from its recent report. Hint: there's a lot of green.
In the midst of our ongoing research on how AI is changing contract management, we encountered an intriguing tool that allows users to create an NDA from scratch — without a lawyer.
Created by AI Tech Support Ltd. and powered by Neota Logic, LISA (Legal Intelligence Support Assistant) “has been programmed to help you and ‘the other side’ (the receiver) find a commercially sensible middle ground for your NDA.” Instead of the usual back and forth over small points, led by biased human lawyers, LISA allows you hash out an agreement fairly quickly (10–15 minutes) through a web app.
Contract Lifecycle Management (CLM) may seem like an application area that should be hardwired to an ERP system. Contracts are the ultimate commercial system of record, so they should be housed in an enterprise-wide software suite, available to everyone, right?
Not necessarily. Far from the elegant, centralized solution advertised, ERP suites have often fallen short. Their generic capabilities are often housed in functionally stovepiped modules that fail to meet the unique needs of various stakeholders. They can describe contract documents and have contract attachments, but they don’t understand the data and meaning of the contract clauses and language itself. This shortfall can lead to workarounds, customizations and frustration all around.
In December, Spend Matters covered SAP Fieldglass’ launch of its new product, SAP Fieldglass Flex. The new offering is effectively a VMS designed specifically for mid-sized organizations. Existing enterprise VMS solutions have tended to be too complex and costly for mid-sized businesses. And although some enterprise VMS solutions may have achieved some limited penetration in the mid-market, we believe none has been (1) designed from the ground-up specifically for this purpose, (2) benefited from best practices knowledge of a leading enterprise VMS and (3) had the support of one of the largest global software players. Given the above, we thought it was important to go a bit deeper into understanding Flex and were able to have a conversation with Rob Brimm, President of SAP Fieldglass, to gather more details about the product.
Artificial Intelligence in Contract Management (Part 4: Natural Language Processing and Machine Learning)
In this final installment of our series on artificial intelligence in contract management, we turn our attention to natural language processing (NLP). In earlier posts in this series, I mentioned chatbots and the Turing test, both of which require NLP. I also mentioned machine learning and the process of classifying text to the domain-specific ontologies that model commercial knowledge. At this point, you may have wondered, “Yeah, but how the heck do I actually model and extract all of this knowledge out of our existing contract documents in the first place?”
President-elect Trump has wasted no time intrepidly wading into numerous policy areas. One notable area of action has been federal spending, where his frequent pledges to cut costs from federal programs has made him seem more like the chief procurement officer of the United States (CPOTUS). Beyond federal spending, however, we as analysts of the contingent workforce and services procurement space have a far more specific question we’d like to address: How will Trump deal with the gig economy?
New Year’s resolutions are a fun, time-honored practice that are often made with the best of intentions – yet, quite often, they melt away like the the gray-brown remnants of snow by the time February and March roll around. However, we’ve resolved to help contingent workforce and services procurement professionals stay on top of their game as we head into 2017. Last week, Spend Matters’ Research Director of Services and Labor Procurement, Andrew Karpie, gave his look ahead on platform-intermediated work trends in the coming year, including possible scenarios stemming from how digital platform intermediation for work and services will increasingly become “a mainstream sourcing mechanism in the enterprise.” So how exactly can procurement practitioners in this space stay ahead?
Editor’s note: This is Part 2 of a post kicking off our new Spend Matters series of personal stories from procurement professionals. Missed Part 1? Read it here.
Another supply chain related crisis resulting from Fred Farmer’s antiquated approach to P2P had to do with controls around costing of finished goods, which were arcane to most of the organization and yet vital for ensuring profit. The weaknesses in Farmer’s costing update processes became obvious during this period of particularly high price volatility. As a manufacturing organization tied to an inflexible legacy ERP, Farmer’s company was based in standard costing, which required frequent maintenance in the form of bill-of-material cost rollups and updates to transfer prices. Typically, this would not be a problem if the organization had not been adding product offerings at a rate of about 300 per month. With a bloated material master, in which only about 4% of finished goods contributed 80% of its revenue, the process for updating bill-of-material costs became severely bottlenecked.
In the first part of this series, I introduced the topic of artificial intelligence (AI) in contract management. Today, I’ll touch on AI itself and the first of its areas that will be highlighted in this series: knowledge representation. AI systems are computer systems that emulate (and even surpass) human intelligence needed to perform valued tasks. The Turing test for an AI expert system is whether it is indistinguishable from a human expert that is communicating via, say, a “chatbot” interface. An AI-based CLM system would therefore be able to embody the collective intelligence of contracting professionals (internal and/or outsourced) into computer systems used during ongoing contracting strategy, negotiations and monitoring.
In case you haven't noticed, artificial intelligence (AI) is becoming a very big deal in business. And there is perhaps no area where the impact of AI systems (i.e., systems that exhibit intelligent behavior) will be felt more than in legal departments and, more broadly, in the area of managing contracts. Consider the enormity of collective knowledge that makes up commercial law and amount of money spent translating the semi-structured “legalese” that enshrouds what should be logical business constructs that sit at the core.
Wherever there is a supply chain, there is risk. Whether that risk is a result of natural disasters or a sub-supplier’s labor violations, uncertainty and surprise are a central element. We started out the year with big headlines in the world of supply chain risk. In January, a fire at an Aichi Corp. steel plant in Japan led Toyota to halt production for a week, which was likely to hurt the company’s sales by more than 80,000 vehicles.
When discussing procurement processes and strategy, it’s hard not to mention procure-to-pay (P2P) or the enabling technologies that go along with it. E-procurement, one of the original technology segments to center on automating and improving procurement, has led to numerous internal improvements for procurement groups; e-invoicing automation has led to substantial cost and efficiency gains for both companies and public sector organizations.
And while both these technologies that form the core of P2P have been around for a while, they’re both far from done innovating. To see why, check out our top five posts on P2P from 2016.