In a pivotal scene from the 2011 movie Moneyball, actor Brad Pitt, playing the role of Billy Beane, general manager of the failing Oakland Athletics baseball team, challenges a room full of scouts grappling with the loss of key players and a limited budget about the problem they are trying to solve.
Billy Beane: Guys, you’re just talking. Talking “la-la-la-la” like this is business as usual. It’s not.
Grady Fuson: We’re trying to solve the problem here, Billy.
Billy Beane: Not like this, you’re not. You’re not even looking at the problem.
Grady Fuson: We’re very aware of the problem. I mean…
Billy Beane: Okay, good. What’s the problem?
Grady Fuson: Look, Billy, we all understand what the problem is. We have to…
Billy Beane: Okay, good. What’s the problem?
Grady Fuson: The problem is we have to replace three key players in our lineup.
Billy Beane: Nope. What’s the problem?
Chris Pittaro: Same as it’s ever been. We’ve gotta replace these guys with what we have existing.
Billy Beane: Nope. What’s the problem, Barry?
Scott Barry : We need 38 home runs, 120 RBIs, and 47 doubles to replace.
Billy Beane: Ehhhhhhh! [imitates a buzzer] The problem we’re trying to solve is that there are rich teams and there are poor teams. Then there’s fifty feet of crap, and then there’s us. It’s an unfair game. And now we’ve been gutted. We’re like organ donors for the rich. Boston’s taken our kidneys; Yankees have taken our heart. And you guys just sit around talking the same old “good body” nonsense like we’re selling jeans. Like we’re looking for Fabio. We’ve got to think differently. We are the last dog at the bowl. You see what happens to the runt of the litter? He dies.
The Odds Are Against You
It’s easy to understand Billy’s frustrations: trying to solve a problem that’s been misconstrued leads to implementation stumbles. A lot of time and resources are put into creating and executing a solution that doesn’t deliver the wins you’re looking for. For an organization, that’s business value. Recommended solutions don’t take root within your organization, value is lost, and then the focus shifts to the new solution.
Repeat and rinse.
What are the odds of the successful implementation of a new initiative? In summary, the news is not good. If you’re heading up a new initiative or implementing a strategy in your organization, the odds are not in your favor. Multiple studies substantiate the rather dismal outcomes of well-intentioned initiatives. Research conducted by others showed how Total Quality Management (TQM) and other programs like it (e.g., Six Sigma) have roughly a 20-40% success rate for implementation. Eighty-five percent of re-engineering programs failed to live up to their expectations. A 2013 Gallup Business Journal poll reported that over 70% of change initiatives fail.
The statistics on the success of data analytics implementation success is following the same trajectory. A 2016 McKinsey survey of over 500 executives representing companies across the spectrum of industries, regions, and sizes showed that over 85% acknowledged that they were only somewhat effective at meeting goals they set for their data and analytics initiative. A Harvard Business Review article entitled “Why You’re Not Getting Value from Your Data Science” needs no further explanation as to the key issue. To round out that list, a 2014 Analytics article entitled, “The Data Economy: Why do so many analytics projects fail?”
These afore-mentioned programs are sound in their logic: they work! So what is driving this notable—and all-too consistent–failure rate?
The Drivers of Implementation Failure
Regardless of the program focus, the reasons for failure are remarkably the same. My research findings for implementation failure included:
- tasks associated with maintaining the bureaucracy of the new program become more important than the thinking skills,
- too much emphasis on tools and terminology,
- organizations lost sight of what the initiative should do
- the inability to create or maintain commitment and,
- the lack of definition regarding the specific problem to be solved.
Analytics Magazine hits the proverbial nail on the head in the last point when it noted, “Most often, a data scientist will collect data and build a model to only, at best, come up with the right answer to the wrong problem – i.e., a problem or question that the customer did not convey.”
This inability to frame and align on the problem that we are trying to solve is a predominant theme, and one that is portrayed in Moneyball. Have we fallen prey to spending money on high-priced batters that (a) we can’t afford and (b) won’t help us win the game we seek to play? Have we taken a moment to fully diverge on the problem to be solved? Are we attempting to implement a solution that failed years ago?
So how does an organization improve the odds of implementation? How can these causes of implementation failure be addressed?
Redirect the Talk from Solutions to Problems
Billy Beane’s insistence to first re-examine the definition of the problem to be solved was spot on. Once the problem was defined, all his scouts’ ‘solutions’ were meaningless. Knowing what you are trying to solve is a critical, do-not-pass-go kind of required thinking before brainstorming solutions. But this is counter to what groups do. People tend to speak in solutions without thinking about the problem or question driving those solutions.
People tend to speak in solutions.
When groups gather to implement a new initiative or create a new strategy, they typically tackle these challenges with unexamined, “old” definitions of the problem. This finding was echoed in a Harvard Business Review article entitled, “Bright, Shiny Objects and the Future of HR.” The authors note that successful human resources initiatives persevere at understanding the essence of the problem and do not just run with the latest fad or presenting symptoms. They compared this to the unsuccessful organization’s approach of becoming quickly enamored with “bright, shiny solutions” and failing to “spend time letting the challenge soak in, studying it from various angles, and understanding it more deeply.” key issue is that unstudied problems are loaded with unquestioned assumptions. The noted scholar Ian Mitroff, in his excellent book, Smart Thinking for Crazy Times, noted that there is more than one way to formulate problems. He states, “Messes are whole systems, a whole set of problems that are dynamically interconnected.” To succeed, he shares how we must explore how the problems are interconnected and closely examine the interactions between them.
Ask The Disconfirming Question
In my experience, leadership teams often avoid the discomfort that can accompany such deliberations and choose instead to move on to the ostensibly easier work of mandating a solution. They rarely explore why it makes perfect sense that a business unit or department will resist implementation. What is the extent to which those who must adopt or implement new initiatives see that a problem even exists?
Ask, “Why does it make perfect sense they will resist?”
Where Do We Go From Here?
The first step in successful implementation is to put aside the brochures, the latest management articles, and spend time diverging on the driving catalyst for a given change. Map it. Debate it. Illustrate it. Be open to being challenged on the assumptions that provide the foundation for each problem frame suggested. Use question-storming methods to uncover the underlying and likely untested assumptions. Ask questions such as “What’s the catalyst that is driving us to consider this initiative?” and “What will be different if this is implemented and why does that matter to us?” And absolutely redirect the focus from solution-speak to problem-speak.
In the next segment, I’ll explore how well-intentioned training programs often associated with new initiatives fail to identify and specify the specific behavior to be changed (telling people to “be more collaborative” will fail in reshaping behaviors). The third and final installment will be a story about bananas—rotten ones, that is—and why many initiatives fail because leaders mistakenly interpreted signs of implementation struggle as indicators of failure of uptake.