Commitment vs Buy-in: The difference between organizational Success and Struggle

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I was told I did everything right.

The business impact was defined, everyone on the VP staff was aligned, and then I presented my project proposal for funding and then BANG! I did not get the resource funding that I requested.

I never understood what had happened. I just felt defeated. It was not like I was not asking for much; the ROI was there, everyone agreed it was the right thing to do. We needed a software engineer to productize a few predictive modeling scripts. This would allow the engineering team to validate their data and build positioning presentations for the Sales team. It would have taken a 5 week process down to less than a week; everyone agreed, but the funding was not granted.

A few years later I read Annette Franz's book Customer Understanding: Three Ways to Put the "Customer" in Customer Experience (and at the Heart of Your Business). Why I failed to get funding became crystal clear. Everyone had bought-in to the change, but they were not committed to the change. Franz used the analogy a hen and pig start a restaurant, which they named Eggs and Ham. The hen is bought into the business, but it's only the pig that is committed.  Poor piggy! [1]

It was clear that the organization was not committed to change. As a result, the funding did not follow and the organization did not benefit from analytic efficiencies.

As I read more and more business articles on how organizations are struggling to adopt analytics and artificial intelligence (AI), it becomes clear that business organizations are not committed to the process of adopting analytics and AI.

Many AI initiatives fail. Seven out of 10 companies surveyed report minimal or no impact from AI so far. . . difficulties with generating value from AI show up in the data as organizational rather than technological.

[2] MIT Sloan Management Review

How many of these organizational difficulties are caused by lack of commitment to the journey, where leaders really only have bought-in to the idea of adopting analytics and AI?

Let's explore what commitment vs buy-in looks like

"We need to change  . . ." vs "We cannot make them do that"  Building a data-driven culture is change management and cultural transformation. Leaders and managers need to establish the vision and the path for the mission for this change. If this is something they want, it needs to be accepted by all. Yes, there are going to be those that do not want to change, but these folks need the choice to either get on the Bus with the others or find themselves left behind. Creating the Bus to show those how to and who has joined is critical to get the organization to make the change and move the organization forward. (The Bus reference is from the Jim Collin's book Good to Great [3])

“We are going to do this..“  vs “Go get alignment..“  To be data-driven, the top leaders need to role-model how to be data-driven. Leaders and managers need to own the passion to rally the troops, vs having someone else do this work. If they do not want to spend their influencing time or resources to make it happen, they are not committed.  In other words with buy-in, the change management responsibility is pushed down the ranks.

"We will learn together."  vs "Go get this information"  For the majority of business (and some technical) folks, analytics, statistics, or data in general are just hard and over-whelming to wrap their head around. It takes a mind-shift on how to think and conceptualize what is being done with data and how it can be applied to business.  If everyone knows that it’s a mind-shift (am I the only one that does not get this???), they will realize that they are not alone and be more open to change.  If management role-models, (or even simply acknowledges) how they are learning or using data to make decisions, the ranks will go the extra effort to focus on making the mind-shift. Management cannot rely on their employees to do what management says and then follow-through, without reinforcement or accountability. It will never happen if it is one or a few people, it needs to be the organization's mission. Management needs to lead by example and reinforce the data-driven behaviors.

Management allocates comprehensive resources vs Ranks need to fight for resources. Developing data-driven behaviors does not come without cost. It is very resource intensive. From understanding what business questions need data to answer them; identifying these data sources; building an infrastructure to ingest, transform, analyze, visualize and consume the data and analytics; training the organization how to understand and trust the results; and finally, building effective business processes, it takes a well coordinated organization to get this work to be effective. The more this work is coordinated, the better positioned the organization is in effectively adopting analytics and AI. This requires full commitment by leadership and management to prioritize what work gets done and knowing what resources are necessary to fully support this work. Once groups are put in the situation to fight for any of these resources, they are focusing on obtaining these resources (in survival mode) vs making the necessary journey progress that is needed. This is a waste of resources in itself that should be focused on building the organization's capabilities.

Key Take Aways

Leaders and managers, who are committed to the analytics and AI journey, are a few crucial steps ahead of those who are bought-in. Their organizations are in a much better position to harness the power of analytics since they are focusing their people and resources together in the right direction. Leaders who are not fully committed to the analytics and AI journey do not make efficient strives, by wasting necessary resources, by not pushing their organization together in a common direction.

As a data professional, it is crucial that you are aware of the dynamics you are up against. If you have leaders and managers who are just bought into this journey, it may be an up-hill battle to receive traction from your work. You will spend more time fighting for resources vs doing real data science that adds direct value to the organization.

Please share your experiences of what commitment or buy-in looks like and how it has impacted your work.

References

[1] A. Franc Customer Understanding: Three Ways to Put the "Customer" in Customer Experience (and at the Heart of Your Business) (2019),  Independently published

[2]  S. Ransbotham, S. Khodabandeh, R. Fehling, B. LaFountain, and D. Kiron (2019), Winning With AI, MIT Sloan Management Review

[3] J. Collins Good to Great: Why Some Companies Make the Leap and Others Don't (2001), HarperBusiness

I'd love to hear from others. Have you experienced the difference between commitment and buy-in? How has it influenced your professional journey?