Many organisations are forced to take a leap of faith. Under pressure from consumers or shareholders they know they need to transform, but they might not have the comprehension, capability, or capacity yet to guarantee the success of such a move. Yet they must jump! This is particularly true when it comes to analytics and AI. In such a position, they can be tempted by advocates of simplistic solutions promising to be the panacea for the organisations’ pains.

Now here is the paradox. In many areas, it is hard to feign expertise. If you have never tuned a machine learning algorithm, written a SQL join, or coded a risk model, people will quickly cotton on if you choose to feign ability. Yet in technology, it can be dead easy to keep up appearances. Usually, regurgitating the latest conference talking points or mentioning a solution featured on a Mystic Square will do it. Some will exploit this to fake credibility, but not all.

Trust me, I own a lab coat. You think you can just buy one of these online? Oh, wait. Photo by Kendal.

When I was only a few years old, I already wanted to help with cooking. I would stand next to my parents, swinging about spices in wild abandon, determined to make my culinary contribution. While I had absolutely no idea what I was doing, you would not have been able to tell from my insistent seasoning. I had my nutmeg, and I would use it too. This is not unlike certain people who will mindlessly advocate a technology, without realising they do not comprehend it.

Modern organisations are filled with well meaning technology enthusiasts who saw that "one cool company" present at that "one exciting conference" — and now they are fully convinced they know the way to go. This is more Dunning-Kruger than diabolical and can easily be resolved. Investing in bringing these people up to speed means their enthusiasm can be channeled in a more productive fashion, such as involving them with the procurement process.

Sadly, there are also those with less scruples who will gladly bluff their way through their careers. For them it is not about finding the best technological solution, but finding one that will serve their own needs. On the benign end of the scale this can mean picking an option that will not require them or their teams to reskill, even if the technology is inferior. On the other end of the scale, a vendor might be chosen based on a commercial incentive or kickback.

One of these will do the trick, I promise. In case they do not, I have another set! Photo by Sara Bakhshi.

Whatever people's motivations, it is important to recognise that we can easily be swayed by forceful technology advocates. Yet if we look deeper, we will often find that those who shout the loudest tend to have the least experience in the matter. When it comes to technology and enterprise transformation, as in life, experience breeds nuance, and this nuance can mean the difference between a best-of-breed strategy and millions of dollars wasted on the wrong solution.

Therefore, let me start this year on a mildly cautionary note. We are past the tipping point when it comes to building interest around analytics and AI. Let us now make sure that we work diligently to deliver positive impact with every initiative, and let the facts drive the direction. Enthusiasm should be celebrated, but in today's day and age, let us be sure to validate expertise and not blindly cede credibility to those who shout loudest. Doveryai, no proveryai!

– Ryan