Don’t settle for horses when you could have dragons

Photo credit: Alyzah K via Unsplash

Sometimes, when we are talking about technology, we quote Henry Ford, who said, ‘If I had asked people what they wanted, they would have asked for a faster horse.’

Except that Henry Ford never said these words. They were first associated with him in 1999, when an article by John McNeece suggested that, ‘There is a problem trying to figure out what people want by canvassing them. I mean, if Henry Ford canvassed people on whether or not he should build a motor car, they’d probably tell him what they really wanted was a faster horse.’ (Quote Investigator gets the credit for the research.)

But people are people and the Internet is the Internet, and the quote sounds like something Henry Ford would say, so we now say that he said it, just as every other quote is attributed to Mark Twain, Albert Einstein or Winston Churchill.

And one of the reasons we keep on quoting the quote (that isn’t a quote) in the field of enterprise technology is that we feel that it is true in spirit: we are asked for the equivalent of faster horses every single day.

If you would like an example, imagine the most mundane project, meeting the most basic business need: perhaps the implementation of payroll processing and expenses using a corporate ERP package. If you are the manager, architect or lead engineer of such a project, you know that you have at your disposal products which have received billions of dollars of research funding and development over many years, and represent the distilled experience of business management in thousands of companies. These days, you also have access to AI enabled workflows and agents, poised to integrate and automate work.

And yet the way you spend your day is arguing over how and whether to replicate the different expenses policies in different business units, which everybody knows should be consolidated and reconciled, but where nobody is prepared to take the hard business decisions. You implement processes and policies originally meant for paper forms in the 1970s and 1980s, and, when you finally get the system working, you make some marginal gains and savings by doing away with a few spreadsheets, generating some extra reports, and automating some manual steps. Faster horses.

And it is not always the case that ‘the business’ displays a lack of imagination and holds the ‘technology’ or ‘digital’ team back. Imagine that you are an end user who has to deal with different information from different business units. You have grown frustrated with typing data into multiple, incompatible interfaces. Furthermore, you know that, if you connect the data, you can understand your customers better. You start building your own solutions with spreadsheets, but you quickly graduate to data management and reporting tools. Your colleagues start to use what you have built and, worried that you don’t have the capacity to support it, you turn to your IT department.

And ride into the mud. First, you are told that the work that you have been doing, using the technology you have been given to do your job and serve your customers better, is ‘shadow IT’ and that you shouldn’t have been doing it. Second, you are told that the IT team could help ‘productionise’ your system (most likely by replacing it), but their portfolio is full right now, so you will need to raise a business case, submit a request, go through the priority setting process and so on. The cycle is yearly: if you start now, you might just make next financial year!

You did more than try to make your own work go faster: you offered the IT department a different way of doing things, a way to activate an empowered community of users to use technology to improve their jobs. And they responded by sending you down the same paths that generate bottlenecks, frustration and delays. Saddle up.

Computing is one of the most powerful inventions of humanity, even before the growth of AI (and we should remember that everything in the current generation of AI depends utterly on classical computing, and is implicit in the mathematics which underpin it – quantum computing is another matter). It offers leaps of capability far beyond that between the horse and the car: it is as if we have a dragon in the basement, if we can only work out how to help it take wing.

Getting into the air requires ambition and expertise: expertise from technical people, who understand just what technology can do; and expertise from business people, who understand just what a difference it would make. Those different types of expertise come together best in multi-disciplinary teams, teams of people who talk to each other, share success, and spark each others’ imaginations in a cascade of escalating ‘what if?’s.

The quote from Henry Ford is inaccurate because he never said it. When we work together we can show that it is even more inaccurate, because people can demand and deliver, not faster horses, but dragons.