Representatives of companies involved in mergers and acquisitions always talk as if there are immediate synergies. But I find it takes at least a year, but normally 18 months, for the companies to “burp” into a somewhat single culture.
Of course there are some multinationals that are good at keeping lines of business separated. However, more often than not, synergies that seemed obvious turn out to be elusive as customers often have done their own best-of-breed selection.
With IoT ecosystems you have to wonder if the smaller members are looking to be acquired. When I worked for a large telecommunications software developer, our specific line of business thought we were a good target for acquisition. I learned the internal opinions did not match up to external thoughts, as one friend commented on our culture this way. “If you look at Cisco, Oracle, and many of the new breed of companies, they are moving in the same direction like a school of fish.
When I look at your company, I see a pilot fish that cleans off the scum of a whale.”
In other words, we could make customized software, not customer software.
Looking back it was a very valid point about the way we built systems for administrators and not for ease of use.
Digital transformation is all the buzz now. But I have to ask what are the risks in looking for synergies that may be based on soft dollars.
When it comes to IoT this can be particularly frustrating, as it’s rare that the code will be used to interact with humans. Regression testing can only look at the requirements of years gone by. As we look to transform business, the models of the past are less relevant.
In the old days it was said you dated your word processor, but married your database. The question I am wrestling with right now is: Can I get away with dating these platforms?
Particularly in the enterprise right now, the wins are very vertical – an industry segment, a security strategy there, and some smart building stuff in between. Do these systems need to be tied into together?
In talking with analytics companies, I keep hearing about anomalies that make it seem like more sources are more important than deep data. For example, a restaurant company finds that spoilage management is the key to reducing the need for pest control. It sounds obvious, but the data came from a corollary of trash pick up with food purchases. And the adjustment was on volume and timing.
In addition, this northern company saw seasonal differences when the snow kept the pest population down and the take out went up. That’s a lot of mixed sources.
Now one logical answer is that the platform is irrelevant as long as the analytics system is comprehensive.
Another is that if the platform does not know what to gather, the analytics system will be useless.
“It’s a balance” feels like a cop out.
Friends on the sensor side point out that they have “all” the information, but they are not sure their customers know what they want, or “know what they don’t know.”
It’s therefore a best practice problem first.
And that feels like another cop out.
So is the statement that “machine learning is the answer.” That suggests that the machine has data to learn from.
I come away from all these talks convinced of one thing.We are a long way from a mature market.
The current emphasis of diving deep into vertical markets makes it hard to imagine the benefits of connections.
James Burke did a BBC series on how lessons in one industry lead to the development of solutions in another industry. My favorite example was that Germany learned how to make rockets based on its beer brewing methodology.
I will continue to try to provide the most horizontal information to companies using IoT because I believe that cross over is the key to digital transformation.
Edited by Ken Briodagh