Own the Unknown? with Tom Davenport and Ian Barkin

Welcome to the first December issue of Further's Own the Unknown? LinkedIn newsletter. Twice monthly, we'll share some of the knowledge we've gained from following, reading, and interviewing some of the most insightful and influential thought leaders on LinkedIn.?

This month our thought leaders are the coauthors of All Hands on Tech: The AI-Powered Citizen Revolution, Tom Davenport and Ian Barkin. Further’s Data Science Principal Keith McCormick will be interviewing Tom Davenport and Ian Barkin on December 10th.

Tom and Ian have been on this journey for some time. We’ll be sure to ask them how their focus on different aspects of the issue converged and led to the book. Tom wrote an HBR article about low-code/no-code development in 2021, When Low-Code/No-Code Development Works — and When It Doesn’t. Ian has produced LinkedIn Learning courses for a number of years, primarily on Robotic Process Automation. Then their collaboration on two coauthored articles, We’re All Programmer’s Now and Harnessing Grassroots Automation led to the book. Except where indicated, quotes are from All Hands On Tech.

What is a Citizen?

A Citizen in this context is someone who develops applications of information technology outside of a formal information technology? group within organizations.

The notion of a citizen is not new. Gartner is usually given the credit, about a decade ago, of coining the phrase Citizen Data Scientist. Low code/no code data science, a related topic mentioned in the book, has been around for more than 30 years. Keith was using Clementine (now IBM SPSS Modeler), and IBM SPSS Statistics in the 90s. The notion of citizens has always brought some controversy, often with the vendors of tools made to empower them in an advocating role, and IT teams being more skeptical. Something that is new about Tom’s and Ian’s approach is how comprehensively they define the citizen movement. It’s not just data science.

The types of citizen developers vary according to the roles they play. They include scouts, who identify opportunities for improvement and change; designers/architects, who develop new and better ways of doing things; developers/automators, who build the applications that deliver those process improvements; and data scientists/analysts, who study, analyze, and report on the status of the old and new processes.

RPA and automation more generally has been developing for many years on a parallel path.?

Companies are increasingly embracing the idea of helping nontechnical staff members — those who have deep business-area expertise — learn to directly automate processes that give them headaches and eat up their time. For instance, human resources employees are uniquely qualified to identify the mundane and repetitive parts of their jobs, such as candidate-tracking tasks, and then, with some training, build automations that will relieve them of chores such as duplicative data entry and data cleaning. (Harnessing Grassroots Automation)

The citizen “scout” is a new aspect to the discussion. We’ll be sure to ask Tom and Ian how common the scout role is in the companies they’ve interviewed.

A case study approach

Anyone who is familiar with Tom’s many books will recognize the case study approach that he and Ian use here. Particularly powerful is the recognition of how sensitive the topic still is. As a reader, one feels like you’ve been invited to sit in on conversations about a topic that is still a bit uncomfortable. One of the heroes of the book has to be referred to by his pseudonym, Mr. Citizen.?

Another hero, Jay Crotts, represents a clear victory for the citizen movement. Those of you that haven’t read the book yet will be pleased that data governance is covered thoroughly. The use cases are not just aspirational - many of these organizations have taken substantial steps to make citizen participation a reality.?

The critical thing, (Crotts)? believed, was finding a safe place to access and store data for citizen use. He told Kappeyne to find a place to put the data, and then data owners—which already existed—throughout the business would determine access to it. He said to Kappeyne at the time, “What will bring people to your platform is where the data is.”

Two Types of Citizen Data Science

We discussed Citizen Data Science briefly at the end of our conversation with Donald Farmer when I asked him to compare/contrast citizen data science with embedded analytics. He shared some concerns. Tom and Ian make a helpful distinction between two kinds of citizen data science, and one is more controversial than the other.

Citizen data science as practiced in organizations really consists of two categories of activity. One might be more accurately called citizen data analysis because there isn’t much science to it. Instead, it involves straightforward data analysis with only descriptive statistics, visual analytics, or perhaps a bit of ordinary regression analysis. Few people seem to object to this idea, as it doesn’t require a high degree of quantitative expertise and creating a dashboard full of bar charts is unlikely to lead to really bad decisions.

The other category might be called real or true citizen data science, because it involves complex data analysis and the use of sophisticated predictive models. This activity has both proponents and conscientious objectors. It requires statistical expertise, and its outputs can be embedded into decision processes that, if made badly, can lead to a lot of trouble.

With a very active Data Science and AI consulting team at Further, we’ll be particularly curious about hearing more about this distinction. Tom and Ian have given several interviews since the book's release in October, and Ian has articulated a distinction between “me” projects and “we” projects. We’ll also be sure to ask about this distinction and how it may overlap with the two kinds of citizen data science.

Upcoming interviews and events

If you haven't done so, follow Further here on LinkedIn. That's the best way to get the latest news. And click on "attend" so that you won't miss the interview. You'll also be able to watch the recording in your LinkedIn feed.

Immediately after the interview, Keith will be flying to speak at the AI Summit in NYC. The session, with Dan Coates is Leveraging AI and Data to Understand Young Consumers and Create Gen AI Experiences. If you are in the area, join to experience one of the largest AI conferences in the northeast.?

We are thrilled to announce two exciting Own the Unknown? guests for early 2025. Matthew Lungren MD MPH , a thought leader in Medical AI, and contributor to Linkedin Learning, has agreed to be our January guest. AI ethicist and author of Responsible AI, Olivia Gambelin has agreed to be our February guest.