Four Eras of Analytics – Keynote from Analytics Frontiers

We were pleased to attend the Analytics Frontiers conference on March 30. The Data Science Initiative at UNC Charlotte conducted the conference, and over 400 people attended the all-day event. The audience was excited to hear from the experts in data analytics. Unlike many other conferences, the audience at this event stayed until the very end. Keynote speakers included David Kiron from MIT, Sam Ransbotham from Boston College, and Tom Davenport from Babson College.

There were many breakout and panel discussions in addition to the keynote speakers:

  • Panel discussion on UNCC’s Data Science Initiative
  • Panel discussion on Big Data – Lies, Damn Lies, and Statistics
  • Breakout sessions on various topics including Smart Cities, Security Analytics, Data Analytics for Social Good, Internet of Things, Mobile Analytics, and other topics (see complete Agenda here)

We were not able to attend as many sessions as we would have liked, as they ran in parallel. For this post, we will focus on covering the lunch keynote address from Dr. Tom Davenport – Four Eras of Analytics.

Four Eras of Analytics

Dr. Davenport described the four eras of data analytics, and how the move to cognitive is affecting our world.

Era 1 — Business Intelligence. He described this as traditional analytics.

Era 2 — The Big Data era. He described this era as where we started seeing online "data products".

Era 3 — Where we are today. Analytics are becoming core to many businesses, and now the businesses are working on expanding scale and scope.

Era 4 – Analytics for automated decisions. This era shows a transition from Analytics to Cognitive, with many ‘knowledge tasks’ being automated. The remainder of his talk was on the impact to people, and future concerns for the transition to Cognitive.

Dr. Davenport explained that automation typically results in a displacement of human workers. Industries that heavily automate display a "race to the bottom" on pricing and profits. In the 1800’s automation replaced manual work. In the 1900’s automation replaced administration and service jobs. Now we are seeing automation replace knowledge work (examples below)

Dr. Davenport suggested 10 knowledge work jobs with automatable tasks:

  1. Teachers/Professors – online content, adaptive learning
  2. Lawyer – e-discovery, predictive coding
  3. Accountants – automated audits and tax
  4. Radiologists – automated cancer detection
  5. Reporter – automated story writing (a North Carolina example is Automated Insights)
  6. Marketer – programmatic buying, focus groups, personalized emails, etc.
  7. Financial Advisor – robo-advisor (example Betterment)
  8. Financial Asset Manager – index funds, trading
  9. Programmer – automated code generation
  10. Quantitative analysts – machine learning

Dr. Davenport explained that technology is the driving force behind knowledge work automation. He identified analytics and Big Data, machine learning, neural networks, and Cognitive computing (like IBM Watson) as contributors to the change.

If you are a knowledge worker, here are the things he suggested you do:

  1. Choose to master the details of the system, and know how to make improvements.
  2. Take a big picture view of computer-driven tasks and decide whether to automate new domains.
  3. Focus on areas that automation does not do well today.
  4. Focus on niche knowledge domains that are too narrow to be worth automating
  5. Be part of it and build the automated systems.

Dr. Davenport concluded by expressing a few concerns. For example, we do not fully understand interconnected decisions well. He cited examples including a flash stock market crash, power outages, and air transportation adjusting to weather events. We need to be able to model dynamic interactions between humans and automated decisions, and have a ways to go.

Data analytics and Data Centers are two areas where North Carolina excels. Thank you to UNC Charlotte for hosting the event, and to all the speakers for sharing their expertise. We look forward to the future and seeing where Cognitive takes us.