The Executive's Guide to AI and Analytics

The Foundations of Execution and Success in the New World

Scott Burk, Gary D. Miner

• Publisher: Productivity Press
• Year: 2022
• ISBN:
  9781000596328
• Edition: 1
• Topic: Business
• Subtopic: Management
• Index: Business

The Problem? Companies are failing to deliver on AI and analytics with over half stating they are "not yet treating data as a business asset". Over half admit that they are not competing on data and analytics. Seven out of 10 companies in a 2020 MIT study reported minimal or no impact from AI so far. Among the 90% of companies that have made some investment in AI, fewer than 2 out of 5 (40%) report business gains from AI in the past three years. And only about 25% of organizations have actually forged this data-driven culture.

Is investment lacking? No. Companies now are spending more than ever in data, analytics, and AI technologies.

Is it a lack of technology? No. There are fascinating breakthroughs occurring on all fronts with image, voice, and streaming pattern recognition on the forefront.

Is it a lack of technical talent? Not really. While some studies cite that we need to train more data scientists, developers, and related professionals, the curve of demand by supply is dampening.

Is it a lack of creating an executable strategic plan? Yes. While there has been a lot of strategic wishing, organizations lack meaningful strategic plans. Specifically, the development of executable strategies and the leadership to see these strategies brought to fruition. This is the problem.

Lack of execution and lack of incorporating key components that align and enable execution of the business strategy to delivery is killing AI and analytics programs. Scott Burk and Gary D. Miner have written this book for executives at all levels who are charged with executing on analytics that need to address this issue. The book provides unique insights into repairing the gaps that programs need to fill to provide value from analytics programs. It complements their three-part series, It's All Analytics! by focusing on leadership decisions that augment data literacy, organizational architecture, and AI case studies.

Chapter 1
Introduction: Sources of Failure

DOI: 10.4324/9781003175759-1

In any given moment we have two options: to step forward into growth or to step back into safety.

What one can be, one must be!

– Abraham Maslow

Where is the artificial intelligence (AI) and analytics revolution? We often hear miraculous stories of cutting-edge breakthroughs. It started with IBM’s Watson’s defeat against champions Brad Rutter and Ken Jennings in Jeopardy ten years ago for $1M. Six years ago, the AlphaGo was the first computer to beat a professional Go player, Fan Hill.

If you listen or read the news, you will hear stories of the miraculous wonders of AI and analytics; how they are changing the world. From this you would think that companies across the globe are achieving miraculous results, right? From LinkedIn to whitepapers, from national news outlets and syndicated news to blogs, AI and analytics have been hot stories for years. Programs are now mature and successful, right?

IBM’s Watson has been plagued with failure and lawsuits. In 2017 AlphaGo was retired.

Not so much. We don’t get the full picture. We don’t read the unwritten story. We read what is available and what is available is meant to sensationalize the stories of the practice. It turns out a large number of AI and analytics programs are not living up to expectations, a number are sick or dying.

Is investment lacking? No. Companies now are spending more than ever on data, analytics, and AI technologies. AI investment in the United States is growing 36% per year, and it is growing faster in some other countries with China growing over 300%. In healthcare, 74% of executives said their organizations would invest more in predictive modeling in 2021.

Is it lack of technology? No. There are fascinating breakthroughs occurring on all fronts with image, voice, and streaming pattern recognition at the forefront. These technologies are driving investment and leading many initiatives, with applications from radiology to autonomous vehicles.

Is it lack of technical talent? Not really. While some studies cite that we need to train more data scientists, developers, and related professionals, the curve of demand by supply is dampening. And, some experts are suggesting the increasing popularity of data scientists may cause an oversupply of talent.

Is it lack of creating an executable strategic plan? While there has been a lot of strategic wishing, organizations lack meaningful strategic plans – specifically, the ­development of executable strategies and the leadership to see these strategies brought to fruition. This is the missing element. The critical element that many organizations lack.

You hear and read the success stories, but these are not indicative of the journey most companies face. What you don’t hear or read is:

• The majority of companies are failing with over three-quarters of their big data and AI initiatives remaining a challenge.
• Over half of organizations state that they are “not yet treating data as a business asset”.
• Over half of organizations admit that they are not competing on data and analytics.
• Seven out of ten companies (70%) in a 2020 MIT study reported minimal or no impact from AI so far. Among the 90% of companies that have made some investment in AI, fewer than two out of five (only 40%) report business gains from AI in the past three years.
• According to New Vantage Partners Big Data and AI Executive Survey 2021, only about 25% of organizations have actually forged this data-driven culture:

  This year’s findings exhibit that challenge to an even greater degree. All questions relating to the long-term progress of corporate data initiatives exhibited declines from 2019 and 2020 levels, a disappointing development.

Eisenhower said, “Leadership is the art of getting people to want to do, what must be done”.

Those companies that have digitally transformed themselves are 26% more profitable than their average industry competitors. But this has required an investment in leadership as well as in technology. Research across the five global industrial revolutions point out one common element of companies that were successful versus those that were not – top leadership was involved at every level of the organization and this leadership firmly focused on success.

There are stories about companies investing in amazing technology, and such might be true, but that is not where organizations are failing. Over 93% of businesses report their people and processes are the problem, not technology.

You will find dozens of books on AI and analytics technology. You will find dozens on the theory and applications of AI and analytics techniques. You will even find dozens more written for data scientists and practitioners of the trade. What you will not find is many books that offer leadership and management, and the candid truth of where organizations are failing and how to overcome these gaps and challenges. You will not find stories of failure and why failure occurred.

Whether you have a mature AI and analytics program, whether you are just starting your program, or whether you have had some success or not, there is a way to be successful in your data-driven journey. There is a way to drive results and return on investment.

Too often analytics strategic planning is done without regard to the plan for execution. Often it is done by a small isolated contingent of leaders without involving necessary design teams, business units, and distributed leaders. Thus, too often, the analytics program suffers. This is not due to lack of investment, but rather due to lack of proper planning for alignment of technical systems, work processes, social systems, and behavioral systems to achieve business strategy.

By 2022, it is estimated that 90% of corporate strategies will explicitly mention information (data) as a critical enterprise asset and analytics as an essential competency.

It is critical that organizations get this right.

We are in an AI and analytics revolution. Organizations must successfully plan and align and then execute. They also need to build into their plans the ability to adapt quickly to external as well as internal forces. If they do this, they should thrive. If they don’t, they will likely not survive.

A Modern-Day Story and the Need to Adapt

She addressed the board of directors. She had been preparing for days. In fact, her brightest minds had been preparing for days. This was not going to be a typical meeting. That was evident from the last board meeting coupled with several one-on-one conversations with several board members. She had to successfully defend her position or she was out of a job.

She was Tricia Garcia and she was the CEO of South State Medical, a medium-size nonprofit medical system with seven hospitals, various facilities, and over two million outpatient visits per year. She followed a ten-year rise and had been at the top for the last three years. She was a shining star, but now she might be a falling one.

The problem? The board had brought her on with a limited set of business initiatives (expand the network, cost containment, and the like). But, most importantly, they wanted her to launch an AI and analytics program. Board members were well read and some had experience with the power of data-driven initiatives. They could not understand her failures.

Susan was not alone. Despite all of the hype around analytics at conferences, from consultants, from software companies, and from marketing engines, analytics are not living up to expectations in the majority of organizations. AI and analytics have been far from successful. In fact, over three-quarters of AI analytics projects never run successfully in operations. Investment in infrastructure is markedly up, staffing is markedly up, and dozens of new master’s degree programs are available at top universities. Mainstream news channels have been advocating the allure, the excitement of it all, for some time. We have heard “we need to be data-driven” for years. Why aren’t we more successful?

Susan’s board is not uncommon. A majority of organizations (57%) believe that AI technology will substantially transform their company within the next three years with the window for competitive differentiation with AI quickly closing. ^* With leaders increasingly seeing AI as helping to drive the next great economic expansion, a fear of missing out is spreading around the industry.

* https://www2.deloitte.com/us/en/insights/focus/cognitive-technologies/ai-investment-by-country.html

There will be many more presentations like Susan’s in the coming years as boards push on CEOs to start new programs or turn around their AI and analytics lackluster results.

“Seventy percent of strategic failures are due to poor execution of leadership, not for lack of smarts or vision”. – Ram Charan

While some companies are not successfully executing their programs, there are companies that are very successful; the gaps are startling. Companies successfully competing on AI and analytics will clearly win out in their industries. In fact, according to Deloitte in a study, the gaps between ROI Overperformers Underperformers (Deloitte’s terms) showed a 60–80% gap that varied across industry.

Therefore, these data-driven programs will only accelerate; organizations that are successful in delivering these programs will survive and those that are not will most likely perish. The keys to success are the right lea...