# Analytics in the Future By:: [[Ross Jackson]] 2024-08-11 Long-distance communication used to require expertise. In the days of telegraphs, a person needed to be able to use Morse code to communicate. One would dictate a message, encoded and sent over the wire, to be decoded and given to the desired person. Later, with telephones, making a long-distance phone call required the orchestration of operators to make the required connections so that people could hold a phone call. Today, many can pick up their cell phone and send emails, texts, phone, or video calls anywhere around the world. One must know very little to make all this nearly intuitive technology work effectively. This might be an effective metaphor for analytics. In the beginning, one needed to be able to do calculations by hand and use distribution tables to analyze data. This required knowledge, patience, and accuracy. With the advent of computers, some of the tasks of computation were automated, but one then had to know how to write computer code to run analytic programs on the data. Less patience was needed as the computer could run the code faster than one could perform the calculations. We are currently experiencing a transition in which computer code writing is less of a barrier as one can either find code on the internet or use AI to generate the desired code. Like the transition from telegraphs to cell phones, the degree of specialization required is decreasing. For the proponents of democratization, this is a good thing. There are fewer barriers to entry; more people can engage in this type of activity. For those who enjoy superiority, this is a bad thing, as the basis of exclusion is eroding. Two divergent paths will mark the future of analysis. One is deeper. A few will be the ones who understand the depth and complexity of writing and compiling AI algorithms. These individuals will be increasingly revered as almost nobody will truly know what they do or how they do it. Most analysts will be interpreters of computer outputs. They will focus on ensuring accurate results, determining which outputs are interesting, informative, and useful, and how to communicate these findings to decision-makers. In the future, analytics will be more about communication than mathematics. This is a significant shift, as very few analysts are currently effective communicators. Ironically, the future of analytics is that there isn’t a future, but futures. Divergent futures. One of increased specialization and technological synthesis and one of increased communication. It will be exceedingly rare, as it is today, for one to be exceptional in both areas of analysis. Those looking to unlock the full potential of analysis should be focused on building powerful dyads and cells that can collaborate, inspire, and challenge each type of analyst to maximize the potential of analysis. It could be useful to add a third member of the cell focused on strategic applications. Such a cell could define the types of answers needed, build the AI algorithms needed to do so, and communicate the findings effectively to those making decisions. Three-person analytics cells might become the basis for powerful organizational analytic units. #### Related Items [[Analytics]] [[Future]] [[Technology]] [[Communication]] [[Strategy]] [[Artificial Intelligence]] [[Organization]]