I attended a lot of conferences last year, including way too many in the month of October alone. While the conferences spanned a wide range of vendors, industries, geographies and customer types, a set of transcendent themes continued to bubble up to the surface, themes decidedly different – real, as opposed to artificial, if you will – that separated them from the buzzy froth that AI was generating throughout the tech market. I first jotted them down back last spring, and they became sort of a bingo card that helped me wade through the BS around the hype of the latest buzzwords du jour that kept dominating keynote stage after keynote stage.
I decided to call these themes, strictly for dramatic effect, the five horsemen of the business apocalypse, though in reality they’re better defined as the five problems keeping CEOs up at night. Or, maybe to be more succinct, the five problems that, if they’re not keeping a CEO up at night, mean that the CEO is sleeping on the job.
1. People: how to hire or procure, train, and retain the people needed to get the job done.
2. Data: how to ensure that high quality, well-governed data is available for transaction and decisions support, including (in case you missed the memo) AI model-building.
3. Process: how to ensure that a company’s stakeholders – execs and worker bees, customers and partners – are able to use the software in your company to do their jobs in the most efficient and effective way possible.
4. Risk management: how to ensure that a regulatory agency, or bad publicity over an issue like an unethical supply chain partner, doesn’t bring down the hammer on a company for some predictable and avoidable misdeed.
5. Spend management: how to do the above, along with the basics of order-to-cash and other core processes, in the most efficient and effective way possible.
As I compiled and then confirmed the list’s validity with every customer conversation, I realized that this list served to reinforce my growing exhaustion with the fanatical insistence that AI is the solution to all problems, past, present, and future. As those pronouncements typically are heavy on future capabilities and light on real business value – other than the value that accrues to, say, the hyperscalers who are going to make a mint on the use of compute resources for building enteprise training models, regardless of the actual value of the models themselves – my list quickly became a way to look at each keynote stage pronouncement in 2024 and see how well it can meet these genuine needs. Absent a compelling reason why an AI offering solves one or more of these five problems now, it’s pretty easy to categorize these offerings as typical technology in search of a problem products that don’t make sense in the real world. (Jon Reed at diginomica compiled an interesting list of AI projects from 2023 that’s a good start for testing the validity of these issues.)
In other words, dear enterprise software keynoters, product people, and marketers, your efforts towards solving the five horseman problems will be met with, in my opinion, greater potential sales and customer success than all that dancing to Wall Street’s latest tune and running those AI and cloud-first flags up the flagpole.
People: We see the people problem literally everywhere, every time we go to the store, call a support line, try to make an appointment, struggle with a late shipment, or otherwise try to navigate our professional and personal lives in this complex, post-pandemic economy. In so many ways, nothing else matters if companies can’t solve their people problems – even staffing and temporary agencies have internal people problems they struggle to solve, never mind solving the people problems of their clients.
While writing job reqs can be a pain, it’s almost quaint to hear about AI-based HR solutions that allow a hiring manager to have ChatGPT ghost-write a job req when demand for candidates has so outstripped supply in so many domains. The issue of procuring the right people at the right time for the job at hand, and then training and retaining them, needs more than just an AI bandaid, and customers across a global continuum of industries desperately need help now with their people issues.
Data: Unlike the people problem, which is a relatively new phenomenon, at least in its present incarnation, the problems with data in the enterprise have been around forever. Issues around data migration are a number one reason why IT projects fail, and siloed data locked into application silos is a huge reason why productivity growth has remained largely stagnant this century despite significant growth in IT spending.
Enterprise data is, to put it mildly, a mess, and a huge barrier to innovation. My favorite example comes from an ASUG member’s talk at last spring’s ASUG Chemicals industry conference. The customer, while acknowledging the need to upgrade its older SAP ERP system to S/4HANA, had put off planning an upgrade that would enable it to be a more effective B2B seller until it had fixed a runaway product catalogue with over one million SKUs. That kind of master data management problem is more the norm than many realize or want to believe. Importantly, this customer realized, wisely, that undertaking an upgrade in order to provide new online B2B services would be a huge waste of time and money without fixing its basic catalogue data problem first.
Ironically, one of the silver linings in the headlong rush to dig into the as-yet elusive massive gains to be had from the current AI hype is that building AI models without clean data is another waste of time and effort. Thus, at a minimum, following the AI hype machine can function as a forcing mechanism for companies to clean up their data cesspools.
Process: People problems + data problems = process problems is a pretty basic formula that highlights what has become a major mess in the post-pandemic economy. The issue of fixing the process debt in enterprises of every size, shape, and industry has come to the fore precisely because the ability to measure, predict, and track the resolution of major competitive issues and the fulfillment of major competitive opportunities can’t keep pace with the changing process requirements relating to customers, partners, and the overall global economy. Fixing everything from poor customer experiences to supply chain glitches to improved ESG practices requires process improvement – regardless of whether the new process comes as part of a single vendor’s product suite or is the result of a project that integrates siloed processes while providing a new user experience.
But fixing the process debt problem is complicated by two major factors: the difficulty most companies have in breaking down the silos that stand in the way of efficient, end-to-end processes; and the fact that there is typically no “VP of Silo-busting” to whom the vision of an end-to-end process can be sold. I looked for those elusive silo-busters at every conference, and even found a few of them – often within or closely aligned to office of the CFO. All of them made it clear that their process problems are only marginally about technology and mostly about people and that elusive change management thing that, like real ROI, seems to be always lurking around an invisible corner.
Risk Management: The next issue on the list is, like data, another evergreen problem that has bedeviled companies for years. Regulated industries have considerable risk regarding non-compliance with regulatory requirements, and many industries, such as the services and hospitality sectors, have traditionally had additional risk management issues related to their liability to lawsuits, among other issues.
The stakes have grown considerably, however, with the need to protect the security and privacy of customer and other data and comply with a growing body of ESG-related regulations. Importantly, these new risk management issues are themselves a moving target, particularly with respect to privacy, security, and environmental reporting issues. In many ways the previous three problems roll up to make risk management even more problematic at a time when the need to manage risk continues to grow at greater than linear rates: Poor data and process quality, high employee turnover and inadequate training can all add to a company’s risk profile. In many companies these more fundamental problems have to be resolved before risk management can be properly dealt with.
Spend Management: It’s almost a no-brainer to put spend management in this list – when has this not been an issue under consideration? – and yet the tenor of what customers have been saying about how they manage capital, revenue, profit, and costs is shifting as the above problems alter traditional notions of how companies navigate the money side of their business. Importantly, siloed technology and business processes have led to siloed spend management, which both impedes financial success as well as serves as a blocker to broader, enterprise-wide solutions.
Decentralized spend management makes it hard to build consensus around new technology and business practices – such as cloud ERP, business networks, advanced planning, and supply chain rationalization – which is why the office of the CFO is becoming so strategic in the effort to break down silos in the enterprise. For better or worse, if the one holding the purse strings can be convinced that all this stuff about people, process, data, and risk needs a steady, enterprise-wide hand in order to be resolved, the political will to solve these problems strategically – as opposed to the tactical bandaids that have been used in the past – can result in creating real, lasting change.
The coming year will probably see some new over-hyped technology join AI as a major mindshare-suck, and Wall Street and the VC community will try to get the rest of us to dance to this new tune. Don’t be lured into thinking that there can be any single new technology that can be grafted on to the mess underpinning these five issues: that’s not how real problems get solved by real companies. Fixing the people, process, data, risk, and spend management problems endemic to the enterprise will need some genuine attention to the hard work of change and people management, which no panacea is ever likely to replace.
I’ll forgive C-level execs for keeping an eye on developments in AI, if for no other reason than the fact that boards have also been infected with AI-creep, and are mandating that something be done about that AI stuff, whatever that is. But not working to deal head-on with the five horsemen is unforgiveable: there should be no great priority than these issues. Otherwise every investment in tech will risk becoming a glossy layer of lipstick on an increasingly homely pig.
Which leads us to that sixth horseman always lurking in the background: Time. Anyone who says time is on their side in the global economy is playing the riskiest game of all.
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