How AI Empowers Service Procurement and Adds Billions to a Company’s Bottom Line
For the modern enterprise, services done well often drive growth. For example, quality IT infrastructure services and/or outsourced marketing can accelerate a company’s competitive advantage in multiple ways. Although it’s sometimes hard to measure the specific outcomes that services yield, they can have a major impact on a company’s results, such as with more successful marketing campaigns, digital transformations, legal wins or other organizational efforts.
That’s why, in recent years, many Fortune 100 companies have significantly increased spend on service providers to meet competitive, productivity and business velocity demands. Companies can’t hire and cultivate enough internal expertise as the work gets more sophisticated and specialized and the opportunities more global. Consequently, enterprise service procurement is now a highly complex and expensive undertaking. Procurement leaders must juggle precise requirements scoping, creating a request for proposal (RFP), evaluating proposals, vetting service provider candidates and negotiating across multiple business purchases.
The Encumbrance of Traditional Service Procurement
While relying more on external service providers’ expertise to achieve their desired outcomes, companies are also facing several formidable challenges. For one, even as some services are becoming more standardized, and by some measures “productized,” there are still variances in their approaches. Each project is delivered differently by unique providers; their teams adjust the work product to match specific customer requirements and circumstances. After agreeing to the scope of work, buyers often don’t know enough about the service they are buying to evaluate differences among providers, and traditional RFPs struggle to generate a comparable set of proposals. It’s quite common to run a complicated competitive bid and end up with two or three proposals that are so distinct that you end up just going with your first instinct, wasting time and effort.
It’s also frequently the case that procurement needs to choose between two deficient options: relying on the same providers they already know or undertaking the burdensome RFP process. It’s unlikely that your go-to firm is the best one for your every need, so sticking with it for convenience means you might miss out on a provider with better niche expertise. In some cases, you might even find yourself paying more because the incumbent provider knows it can take advantage of your existing dynamic and move its best people elsewhere to impress a newer or more demanding client.
The time and resources spent on traditional service RFPs also delay the business benefit of the service and consume a lot of corporate cycles that could be better applied elsewhere. In many cases, the RFP process can’t be done fast enough, given a business’s timeline for execution.
Services are also about people—their experience, their work styles, their personalities. Who will fit well in a given situation is context-dependent. It can be challenging to accurately evaluate contextual fit regarding new providers with whom an organization has no familiarity. The quality of the service experience can also vary depending on the providers’ incentive to serve you. Do they see it as a one-time deal or building a relationship? Realistically, knowledge workers chase opportunity wherever it goes, so keeping them motivated to give you their best effort every time can be tricky.
AI Shifts the Procurement Dynamic
The advent of artificial intelligence (AI) presents a transformative paradigm shift in the service procurement dynamic. AI can cut down the time involved in procurement and improve the quality of every step in the process. For example, whenever a service provider is briefed using a digital scoping tool, the same consistent brief can be used with other providers and made available for similar projects in the future.
Some AI tools can choose from a library of relevant templates so that buyers can more precisely scope needs and more efficiently write briefs. Some sophisticated tools go even further, using dynamic questions that guide buyers in creating a customized “Smart Brief” by using prior knowledge from similar projects. This increases the quality of proposals and enables consistency among even bespoke proposal formats that make submissions easier to compare and assess. It also inherently shortens the decision-making process; what previously might have taken weeks or months can be done in a few days.
AI can also readily match the best service provider candidates to a bidding opportunity. Most of the time, new service providers are sought after when the primary user is extremely unhappy or disappointed with an incumbent. Because incumbents can be so deeply entrenched in these partnerships, it’s often a big deal to change, even if their performances are mediocre. Better but smaller providers might often go unnoticed simply because corporate buyers have no knowledge of their performance or because the smaller businesses can’t take on the massive administrative burden of RFPs.
AI-based systems can overcome this disconnect, allowing customers to enter real-time feedback about their experiences with all providers—large and small—throughout the service engagement process. Later buyers can reference that information to know how previous assignments went—think about it like a review on Amazon. The AI engine can also use that input to rank provider suggestions and propose those providers most likely to be the best fit for each project’s unique requirements. The continual feedback loop serves to motivate and manage service provider performance.
Lest this seems too one-sided, digital sourcing offers many benefits for service providers as well. AI-based platforms can well serve any provider organization that is delivering great work for its customers. Better transparency on actual performance and skills matching can be a boon for the best service providers, regardless of their size, because expertise can be recognized at a granular level. Service Providers will be rewarded for quality or value and not sheer scale, administrative efficiency, or marketing prowess. In this dynamic, incumbent suppliers might also be more likely to up their game; they may even see increases in revenue and profit from a given customer account because digital sourcing will eliminate lots of wasteful work and enable them to win more projects faster and with fewer resources.
The Procurement Leadership Opportunity
Digitization in our lives as consumers has far outpaced that in business-to-business (B2B) commerce, but B2B will catch up in the next several years. At the cusp of this paradigm shift, procurement’s early adoption of digitally transformative technology can have far-reaching benefits for the entire company. Beyond the direct benefits of removing inefficiencies, lowering costs and simplifying buyers’ lives, AI and digitization will free up bandwidth throughout organizations to improve the substantive quality of the work they can do for their customers.
By my estimate, there is easily an opportunity to double the return on services spend while also substantially reducing costs. That means the average Fortune 500 company, which spends a few billion dollars on services, can add that to its bottom line.
Although there have been massive advances in technology, many organizations are not taking advantage of them because of the associated change management challenges. Many digital transformation efforts falter because their architects hesitate to undertake big steps all at once. Fortunately, digital transformation within procurement is easier and less risky than changing; for instance, the sales or service model that involves a company’s customers. At the same time, such procurement transformation offers large-scale rewards for both buyers and service providers. All this should embolden procurement leaders to move faster and perform better across all fronts.
What (Else) IT Procurement Professionals Must Know about Data Center Hardware Maintenance RFPs: Part Two