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  • Madeline Weiss, Director

Recap of our January 2020 Meeting for Senior Technology Executives (Advanced Practices Council)

Advanced Practices Council members – senior technology executives across industries – gathered in Miami in January to continue learning from exemplary researchers and practitioners (including themselves) on topics they voted as high priority for their future success.

Although at first glance the topics explored at the January meeting may appear unconnected, a closer look reveals a clear relationship. Mark Polansky, Senior Client Partner in the Technology Officers Practice at Korn Ferry, introduced this relationship when describing the changing role of the CIO.

Changing Role of the CIO

Mark Polansky, Senior Client Partner at Korn Ferry, reviewed how the role of the IT head has evolved over the last 70 years from tab supervisor (1950s) to data processing manager (1960s) to MIS director (1970s) to Vice President of Information Systems (1980s) to Vice President and Chief Information Officer (1990s) to Vice President or Senior Vice President and Chief Information Officer (2000s) to Senior or Executive Vice President and Chief Information Officer (2010s).

These changes in roles and titles can be explained by the increasing role of information technology (IT) to not only reduce the bottom line but also to increase the top line. And, in some cases, IT has enabled company growth through creation of new products, services, and business models.

Mark compared the top 10 competences needed for success in 2003, when he wrote an article for CIO Magazine, with what he considers to be the top 10 competences needed for success today and the future. He concluded that they are the same. The CIO must create value and remain relevant. CIOs must become self-disruptive – driving themselves and their organizations to adapt, collaborate, and excel in disruptive times.

That’s the relationship among the topics at the January meeting. Three of the sessions focused on technologies that have the power to disrupt. Advanced Practices Council members want to understand both how these technologies can disrupt and how to think about leveraging them to do so.

Strategic Considerations in Leveraging Blockchain Technology

According to Dan Conway, University of Arkansas professor who conducts blockchain research, we are moving towards an Internet of Value that allows us to seamlessly transact value – money, goods, services and other assets – across organizational boundaries over the Internet without relying on trusted third parties.

Blockchain software is shared among all organizational partners. Authorized parties run the same software and maintain an identical copy of the digital ledger, which is distributed to all authorized parties in the network. Instead of relying on trusted third parties, a blockchain solution uses cryptography and computer algorithms to perform truth attestations. Smart contracts, which are computer algorithms that codify agreements, automatically execute agreed upon terms. As the foundation for building the Internet of Value, blockchain has the potential not only to improve the efficiency and effectiveness of transactions, but to disintermediate industries in unforeseen ways.

Dan’s research concluded that blockchains are currently not being used to a significant extent in the U.S. There is much more use in countries such as Estonia and a majority of blockchain patent holders are outside U.S. China is an example of a country with more patents than the U.S. Within the U.S, top patent holders are IBM, Accenture, Mastercard, Capital One, Bank of America, and Intel. These companies recognize the potential business value of blockchains, including lower transaction costs, faster settlement times, better transaction visibility, immutability of records, lower vendor opportunism, and better cybersecurity.

Dan identified the mind shifts required for successfully leveraging blockchains: from command and control to shared governance, from data residency within the enterprise to data residency on other enterprise nodes, from mutable data to immutable data, from agreements managed by people to agreements managed by computer logic, from transactions through trusted third parties to transactions directly with trading partners, and from proprietary to open source code.

Although the technology that powers blockchain has been available since 1999, opportunities to innovate to gain business value have recently evolved. Dan concluded that the Internet of Value powered by blockchains is here to stay. Each enterprise will either help architect the future or risk being victimized by it.

Humanizing the Machine with Language: Five Steps towards Communication

Artificial intelligence (AI), which Kristian Hammond researches at Northwestern University, is not a monolith. The primary applications of AI are machine learning, natural language processing, deep learning, facial recognition, process optimization, recommendation systems, robotics, self-driving vehicles, personal assistants, and predictions.

AI is used by businesses for fraud detection, customer qualification, supply chain optimization, market/ customer insights, automated communication that explains what’s going on in the data set, price/ sale predictions, cyber-security, and resume filtering.

Systems with AI are designed to perform actions that, if performed by humans, would be considered intelligent. What characterizes human intelligence? Humans can make decisions, understand language, draw conclusions, recognize situations, explain the past, understand the present, and plan for the future. We can learn from the past to characterize the present and predict the future.

Machine learning needs to work in the same way. Fortunately, we now have the large volumes of data required for our machines to learn. For example, Google uses AI and large volumes of data for self-driving cars and Allstate can set insurance rates based on driving data captured from subscribers through sensors in their cars.

Currently, language is the hallmark of human intelligence. It allows us to connect with each other, explain the past, communicate the present, and project the future. Although Kristian is confident that computers will ultimately equal human ability to deal with language complexity, computers have not reached that point. Kristian pointed out ways that machines can create information from spreadsheet data as well as the many ways they cannot. For example, machines can’t explain why Albert Einstein won the Novel Prize from volumes of data or determine whether lawyer case loads are balanced or whether judges prefer large companies.

Kristian recommended an approach for getting started on gaining business value from AI:

1. Develop or purchase a tool that supports the task to make the data and process explicit.

2. Track users’ actions and tie them to conditions under which they were taken.

3. Train your system, tying conditions to actions/decisions.

4. Test the system.

5. Transform the tool from one that supports user action to user verification.

Cost/Benefit Analysis for Proof of Concept Pilots for IoT-Enabled Projects

We’ve done cost/benefit analyses and proof of concept pilots for years. What is different when projects involve IoT-enabled devices? According to Michael Goul at Arizona State University, we need to consider network effects that will occur when IoT devices proliferate. We also need to consider a wider range of work streams (e.g., business integration, sensors, edge and gateway devices, cold-path analytics, hot-path analytics, data storage, dashboards, IoT privacy and security considerations, and IoT user interface and access) that could be affected. Michael pointed out the risk of not considering each of these workstreams to your IoT-enabled initiative in the proof of concept pilot.

Michael then presented a specific example of a cost/benefit analysis he was asked to help create on a proof of concept pilot for a global financial company in the credit card business (XCard).

XCard faced a proliferation of IoT devices that customers want to use to pay for products and services. Its existing system for certifying new devices involved people who were Xcard experts. The company recognized that the current system couldn’t scale to meet the expected volume of new IoT devices and partners. It needed to add more self-service capability to scale the certification process and asked Michael to help determine the appropriate dimensions for a proof of concept pilot for a new system. The company wondered what specific business benefits it could anticipate and what it would take to integrate IoT-enabled system capabilities into the business. In essence, XCard wanted to ensure that the proof of concept pilot would sufficiently demonstrate the anticipated business value, considering such elements as network effects, when later scaled.

After walking us through the stages that XCard took to properly launch the proof of concept pilot, he made several recommendations: (1) when planning a proof of concept pilot, consider the 9 work streams and five lifecycle phases that he introduced to XCard and (2) take network effects into consideration when designing proof of concept pilots.

Putting it all Together

Successful CIOs will be self-disruptive, to use Korn Ferry’s term. They will drive themselves and their organizations to adapt, collaborate, and excel in disruptive times. And we know that there is more disruption ahead as new technologies and ways to leverage them for competitive advantage proliferate.

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