If you follow this blog at all, you know that I work tirelessly trying to piece together tomorrow’s technology with the challenges of today to help organizations grow; by creating new value propositions and better customer experiences.
The world we live in is being re-architected into an increasingly understandable collection of atoms, bits, and pixels. The infrastructure for the next generation of progress is being laid.
First came roads, then railroads, then telegraph, then telephone, then broadband, then wireless and satellite, and now everything is in the process of being “connected”. These new connections are enabling unprecedented speed. Yesterday is continually rendered obsolete.
This connectedness is leading to fresh visibility to the world around us. There are literally new use cases emerging every day out of the sea of millions of trials and errors that yield no or inconclusive results.
There are many things that need to come together to make something a success. Proper planning, strategy, execution, and often a bit of serendipity comes along and make something magic. Forces that are beyond our control align to yield tremendous results.
Conversely, there are dozens of other factors that can conspire to get in our way. Any one of which will deflate or impede progress or results.
While we frantically explore the opportunities that the Digitization of Everything, machine learning, and predictive analytics will bring, it’s important to remember that the human brain, by comparison has over 100 billion neurons. For reference, in a recent experiment, it took nearly 83,000 processors grinding away for 40 minutes to simulate 1 second of a portion of brain activity.
While I contemplate the years of hard work that many of the social and community vendors have invested, one giant question remains:
“Why hasn’t there been more adoption?”
Under the layer of a collection truly amazing technology, there are core challenges that are deeply ingrained in us as individuals, in societal norms, in organizational culture.
They are the deep rooted drivers of human motivation. They are the ways that people naturally communicate and self organize. Technology is simply an enabler of the core factors at work, and the best technology in the world won’t solve a leader’s toughest challenges.
“You can try and read my lyrics off of this paper before I lay ’em
But you won’t take the sting out these words before I say ’em”
Marshall Mathers aka Eminem said these lines and there’s an important lesson here. The same tools, and the same data in different people’s hands will yield dramatically different results.
Moneyball has been referenced ad nauseum and Billy Beane has made a nice little career out of speaking on how the Oakland A’s leveraged analytics to understand things about baseball that the old school didn’t know. This understanding helped the Oakland A’s compete effectively with teams that had immensely more financial, physical, and human resources.
What I don’t think is mentioned enough is that given the same data:
(1) How many general managers would have had the guts to spend early draft picks on guys that weren’t even on other teams draft boards?
(2) How many other GMs might have formed a completely different strategy based on the data and the understanding of it?
It’s also important to know that the Moneyball story was simply a snapshot in time. In fact, in was more than 10 years ago at this point. The game goes on. The world moves on. New data, new strategies, new leadership methods are being applied right now.
The whole world in undergoing a great transformation, and most leaders are being forced to experiment and make bets in landscapes that they don’t totally understand.
Maximizing points per attempt
Keeping with sports for just another moment, I read a fantastic article this morning in the Wall Street Journal about how the Miami Heat had devised a strategy to maximize their 3 point attempts from the corner of the court.
Why? Because they learned that because of the court dimensions, the 3 point line in the corner of the court is 1 3/4 feet closer to the rim. After some analysis, they also learned that shooting from this spot had the greatest value per shot than any other place on the floor except for right next to the basket. This data, given to every team, would likely yield different results. Some would ignore it. Some would note it. Some would make some minor changes. The Heat aligned their personnel, their game strategies around these facts to garner an edge (in addition to the fact that they may have the greatest basketball player of this generation on their team).
Another important thing to note, is that the team has come together repeatedly under a common theme of sacrifice under Pat Riley and Erik Spoelstra. Sacrifice has been embedded into the culture. Many of the superstars on that team have sacrificed money, playing time, shots, and their best talent to help the team. It’s the primary lesson here.
The opportunity to gather new types of data, look at them in new ways, derive new meaning from them is one thing. Taking action is yet another.
But it’s the other 70% of the equation that is the hardest part; getting people to believe, giving them a chance to meet their personal goals, getting them to buy in, creating a great culture, and finding a way to amplify individual and collective talents are still the biggest leadership challenges in this era of big data.
| This post was provided as part of the IBM for Midsize Business program, which provides midsize businesses with the tools, expertise and solutions they need to become engines of a smarter planet. I’ve been compensated to contribute to this program, but the opinions expressed in this post are entirely my own and don’t necessarily represent, nor have they been influenced by IBM’s positions, strategies or opinions. |
