Anyone who has followed the career of Wayne Gretsky knows his answer to why he plays better than others: Others skate to where the puck is … he skates to where the puck is going.
Today’s customer engagement game is a lot like this. Most of today’s progressive energy companies are busy diagramming and analyzing the customer’s journey as if that was the true target. They are not studying where the customer is going, at least certainly not as carefully as true competitive businesses.
Utilities should be studying today’s connected home as an early adopter indicator of where the energy relationship is going. Anyone who does quickly learns that energy efficiency and even demand response is not where customers have interest. It is all about convenience and control. It is all about life simplification.
But, anyone who does study this also finds that today’s technology is way too complicated to get “over the chasm” as the book about this marketing challenge analyzes. We have to get past today’s technology … and we are.
You probably did not notice that AT&T and Verizon have just released an alternative to our Wi-Fi dominated perspective. There is absolutely no reason for a thermostat or any in home control to rely on such a high bandwidth approach. This new communication channel is going to revolutionize our approach to everything the energy industry cares about … everything. Wi-Fi is overkill for our industry. And, by the way, the data costs for these services will be less than a $1 a month and almost all of the US is covered by this service … right now!
Customers are also on a rapid migration away from desktop and laptop devices to mobile … everyone knows that. But the way they use the phones has eluded most … they are no longer “keyboarding” to interact. They are now mostly voice based.
Check this out in your own life. See how you use your phone to find things. Study how you check on flights, find restaurants and businesses and even navigate traffic.
We have been busy getting ready for this next puck location using an easy common vehicle to learn how customers want to interact on energy issues. We now have a skill for the Amazon Echo which is conservatively estimated to be 10 million devices in the US.
So, the puck is moving in very different directions.
A LinkedIn posting from one of my friends had this picture in it indicating that his firm “hit the mark!” That made me think of some funny stories of people seeing where the arrow landed and then painting the bullseye around it … marking the hit.
Cute as this might be, managers learn very quickly that employee morale and productivity depend heavily on an identifiable and achievable goals and objectives. They use the term stretch goals to specifically identify things that are possible, but would require extra levels of effort. Over time, as the team sees progress and refinement of the way they work together, short term tracking against these goals and objectives can be extremely beneficial. Working smarter, not harder, is of course necessary and uplifting in this model.
Unfortunately, not everyone is necessarily on board. Some may want to coast and let others do the work. Some may even resent the goal setting process and want to sabotage the team so that the expectation is lowered. Good leaders will not stand for this and normally will confront these bad actors, counsel their behavior, and where necessary remove them from the team. As the phrase goes, one bad apple can ruin the barrel.
All this can get tiresome in a business world where everything seems uncertain and changing. Customer expectations keep rising and shifting. They don’t seem to appreciate all the hard work that went into attempting to make them happy.
So, when all else fails, is the best thing to do is to paint the bullseye around wherever the arrow landed and declare that success? After all, finding all the things that are moving in the right direction and weaving them together as a narrative indicating how that was a result of your good work can seem to make sense.
When this is simply creative writing, the team scoffs and will rebel. If this is simply to bide time until something emerges as a productive strategy, it can be beneficial. But, the key here is that it is the creative point of view looking at what moves the organization in the right direction … which then leads it further down the road to what really does work.
Small steps, but steps never the less. Sitting still and painting the bullseye on a stationary point of view is deadly.
As you might well imagine, our family is a mini Big Bang Theory: I am a chemical engineer married to a physicist with a son who is finishing his degree in computer science. Conversations around the dinner table can be almost anything from generational differences on political perspectives, to comparisons of communication styles, and of course the latest update on the video gaming world.
Last night we talked a bit about the media, which of course loves to cover things that will attract followers. The editor’s rule, “If it bleeds, it leads,” sums up their fascination with violence and fear-based stories, and the song Dirty Laundry sums it up so well. As we were finishing our conversation, I commented that energy is no longer on the minds of Americans, and I gave him a bit of history lesson about the legislation after the two Arab oil embargoes in the 1970s where gasoline was rationed and speed limits lowered to 55-mph.
He was shocked to hear that we repealed the 55-mph speed limit even though it clearly saves energy, money and lives because car wrecks are less fatal. I gave him a short history lesson about the Fuel Use Act that forbade natural gas as a baseload fuel in power plants … and of course a bit about nuclear, which still powers our navy’s large ships.
As I was finishing this I commented that few today knew very much about how we got here, and like the Holocaust and other tragic events in the past, forgetting history almost certainly dooms us to repeating it.
I commented that today’s preoccupation with solar and wind seems to forget about the “rest of the story” to keeping the lights on and that the idea that batteries would save the day is a bit myopic and costly.
Finally, I suggested an informed dialogue on this to truly develop a national energy strategy and he blurted out: “Nobody cares about things like this. People want to talk about health care, jobs, and sports.”
He may be right, but if that is true, we are in a very bad place and doomed to see history repeat itself.
Ali Rahimi, a researcher in artificial intelligence (AI) at Google in San Francisco, California, took a swipe at his field last December—and received a 40-second ovation for it. Speaking at an AI conference, Rahimi charged that machine learning algorithms, in which computers learn through trial and error, have become a form of “alchemy.” Researchers, he said, do not know why some algorithms work and others don’t, nor do they have rigorous criteria for choosing one AI architecture over another. Now, in a paper presented on 30 April at the International Conference on Learning Representations in Vancouver, Canada, Rahimi and his collaborators document examples of what they see as the alchemy problem and offer prescriptions for bolstering AI’s rigor.
“There’s an anguish in the field,” Rahimi says. “Many of us feel like we’re operating on an alien technology.”
The issue is distinct from AI’s reproducibility problem, in which researchers can’t replicate each other’s results because of inconsistent experimental and publication practices. It also differs from the “black box” or “interpretability” problem in machine learning: the difficulty of explaining how a particular AI has come to its conclusions. As Rahimi puts it, “I’m trying to draw a distinction between a machine learning system that’s a black box and an entire field that’s become a black box.”
I have blogged about this in the past. The idea that you throw all your data into a big box and process it to come up with true insights is largely hogwash. I have spent most of my 50 year career on this subject and proven over and over again that you must first start with a hypothesis and test it to see if there is a relationship. In most cases, as you do this, you find even what you thought was a simple relationship is more complex. Then, once you truly know what is true, you can begin to build a learning algorithm that will separate the data into groups of true and false.
If your organization has a big data initiative, please reach out to me and let me help you before your black box thinking kills your credibility.
We have had a running battle with these little critters, attempting to buy bird feeders that claim to be squirrel proof. I thought I was oh so clever hanging the feeder from wire fishing leader that was so fine I never thought a squirrel could climb down to the feeder. And, for a while I was patting myself on the back … until today.
The picture tells the story. The feeder supposedly has a wire mesh frame around it that allows birds to get into the feeder but was supposed to keep squirrels out.
Well, nobody told the squirrel.
Which reminds me of the phrase: “where there is a will there is a way.” Perhaps it is time to recognize that this is the essence of the problem today with innovation and progress. It is not about monetization or journey mapping alone … it is about the will to do something even when it is clear there is a compelling business case.