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Showing posts from August, 2018

Deep adoption; four simple steps

The parallels between trips I made to Daqing, China two decades ago and behavioral observations today around digital transformation are surprisingly similar.   When I was last in Daqing the population was approximately 1 million.   The roads in this remote city were filled mostly with mule drawn carriages and bicycles, very few automobiles. One evening, while eating God knows what, I commented to Chung, our host and translator, "it must be difficult for people not to have automobiles".   Chung responded, it is hard to miss something that you do not know. That's it!   Most individuals in today's enterprises may only use a few pieces of technology; a transactional system (CRM, Accounting, Work order management), a communication system (typically email and or a messaging service, Word, Excel, PowerPoint), and possibly a special purpose application (AutoCAD,etc.).   While I have my "broad stroke paintbrush" in hand we might as well throw out that odds

Magnificent Models | what are you predicting?

The next agenda topic in our executive meeting was IIoT and predictive service. Avid Andy had a feeling that this was going to be a controversial    topic as there was a lot of ambiguity surrounding the definition of data science-based modeling.   This was an opportunity to jump right in and start a brief discussion on the meaning and impact that data science-based learning models could have on the organization.   He began by defining a couple distinct types of models: The market today is filled with lots of misleading information, our competitors all say they can predict, we ourselves have manufacturers stating that they can also predict, and our customers have an expectation that we are predicting. My question is, predicting what? Aligned to which customer outcome? If we do not have a clear picture of all the elements combined with the customer outcome all we will get are unintelligent responses such as your automobiles "check engine

Science and Service | is AI cultural?

Irene was beaming with pride this morning as she shared the conversation last night with her daughter Izzy. One of Izzy's college courses was to conduct research based on a handful of Harvard business studies. At a high level these studies were comparing organizations from three different approaches; keep doing what they're doing, except change but only incrementally, focus on changing in industry by deliberately disrupting the status quo. People were gathering as Irene began to play back the conversation. Mom, exclaimed Izzy, after listening to each bit of explanation on the three Harvard studies it was quite difficult to make a decision on which one was correct. The first example; "leave the business alone we are making money" made some excellent points, continued Izzy, however I really felt as though the rationale had much stronger value in the past and was not preparing organizations for our high velocity changing future. The second use case, "incremental