Cowboys & Cars
“It’s like Groundhog Day” is embedded in our lexicon as a substitute for something that is either monotonous, repetitive, or a bit dumb, like making the same mistake over and over. I understand that, but if you watch Groundhog day, and see past Bill Murrays perfect ‘I can’t be doing with this’ dead pan facial expression, there is a great sub-text. How do we get past same-old same-old mindset and get into learning and adapting. How do we wake-up every morning – quite literally – to reality?
So I’m reminded of a joke / business story / hidden meaning / “It’s like” one liner, that I can neither remember the proper story to, nor the punch line. But I always remember it as “it’s like trying to sell a car to a cowboy”. Bits of the story include a cowboy whose horse has died / been put out to pasture. The ranch owner / horse salesman asks the cowboy what characteristics he’d like for his new horse, to which the reply is “A faster horse”. The Ford salesman across the dusty street is hollering, trying to sell the 4 wheel dream. “Nope, just a faster horse sir”. Same-old.
When I ran a full-service Partner team a few years back, I always likened this kind of challenge in the Analytics and BI space. “What reports would you like” was never the right question. “We’d like faster reports please!”. Instead, “Look at the amazing insights we can bring to your business with these new tools” [Power BI et al.] was always the better approach. You had to pull the demand. Tease it out. Do not ask for requirements, but sell the dream, the capabilities.
That’s all a long way of saying that if you have something new and innovative, it is a much harder sell than old and familiar, despite your confidence in its advantages and merits. The brave (car salesman) keeps hollering from across the street, but the safe customer keeps buying more horses. Buyers tend to favour none catastrophic decision making. The horse is reliable. The car is a stupid idea. Until it isn’t.
Tipping points are hard to predict. Do you let the early adopters take the hit, but risk missing out on the competitive advantage that they might benefit from? I confess it’s a hard one to accurately reconcile. You occasionally have crazy outliers, like Apple’s refusal to support Flash, despite being the go-to in web design. History shows that Apple backed their strategy and won out, and Flash was gone in, well….And when James Dyson pitched an $800 vacuum in a necessity purchase market, not many investors were quick to write a cheque.
Now I don’t come with the kind of arrogance that suggests our endeavours at JOE can bend consumer behaviour with Apple or Dyson like forces, but I do believe in the paradigm shifts that new technology affords us, and in the advantages that it can bring. Not for the sake of it, but because technology opens up doors to solve problems in a moment, that have been generational in the making. Some of these problems are so embedded in our culture that we don’t even recognise them.
Have you ever done a lessons learnt after a project? Me too, plenty. But now I’m looking at those sessions with a more critical eye. When the post-it note goes on the board with “not enough time for training”, we note down , “must allocate more time in the project plan for training”, or something akin. Wrong answer. Or the wrong question. How about, how could we do the training differently, or better, or, what other approaches could we have taken? Substitute ‘training’ for other project elements. Code. Testing. Data migration. Our answers are usually to do more, allocate more. More resource, more time. Rarely do we ask how? Or why?
At JOE, we are definitely on the innovator side of the debate. I like to think we are asking a lot of how and why questions. We are the Ford salesman hollering at you from the other side of the dusty road, whilst you saddle up your horse for a test ride.
Perhaps there are some credible outcomes of the industry asking better questions, like agile methodologies. But it’s at a rate of change and adoption that somehow compromises its very intent. Technology is no longer a platform, it is iterative, almost heuristic. Our methods of learning and implementing have to align.
Groundhog Day was a brilliant movie because Bill Murray adapted. He adapted every day, and when it didn’t work, he adapted some more, every day, until he got the girl. Andie MacDowell is quite the motivation, I’ll give you, but if those of us at the coal face of delivering technology are to have any chance of keeping up with the pace of technology itself, we need to adapt in Murray like time frames. What better way than to use technology itself to evolve our methodologies and strategies?