The last time you were flying internationally, did it occur to you how remarkable it is that across 195 countries, where 7,000 languages are spoken, everyone agrees on the same 24-hour clock? Railway and military operations initially drove the adoption as a way to avoid confusion and ensure coordinated operations. Other businesses such as financial trading then followed suit. 

Did everyone immediately agree on defining each day as 24 hours, or dividing their nations up into as many as 11 time zones? Absolutely not. Although the process of standardization started with the ancient Egyptians, then spread more broadly during the Middle Ages with mechanical clocks, it wasn’t until the International Meridian Conference in 1884 when a 24-hour universal day was established. This would give rise to Greenwich Mean Time (GMT), which took several more decades to become fully adopted around the globe. The point is, the incentives each city and country could share by agreeing on formal time divisions far outweighed the benefits of more provincial, isolated thinking.

In the world of today’s enterprises, what does it take to reach the same level of universal consensus about a data and AI transformation? Turns out the secret to success also involves shared incentives. 

Shared incentives, shared success
Shared incentives play a vital role in business. In the case of time zones and clocks, military victory was the first incentive, followed quickly by international commerce. This demonstrates that when the benefits of incentives are self-evident, well-defined and executed, they drive amazing results. But why?

  • They operate like a contract, creating accountability.
  • They define a North Star that everyone is marching toward, whether that’s a customer-facing goal or a program to support an internally developed tool.
  • They are explicitly a part of annual goals and objectives; they even appear on kickoff presentations at the beginning of the year because they’re considered that important.

Unfortunately, shared incentives are often absent from data and AI transformations. They simply aren’t viewed as key steps in the process, leaving the CDAO to aspirationally operate without sufficient support.

Four essential steps for success 
What some organizations call strategic project planning can quickly become going through the motions, unable to drive real results. At a minimum, these steps are required to put a transformation on track and prevent it from going off the rails.

  1. Strategic alignment. First and foremost, a transformation should align with an organization’s strategy, goals and objectives – not just within the data team. This is a great place to start. Consider a goal of “be the product of choice in the market,” with an accompanying objective of “grow new customers by 10%.” A data transformation can align to this goal by assimilating the best customer and prospect data, ensuring that definitions for customer, new customer and market share are agreed upon, and providing the most relevant insights via predictive models or dashboards in easy-to-consume formats. The focus of data, analytics and governance must have that tight connection with the overall business strategy.
     
  2. Across-the-board sponsorship and support. Having a C-level owner such as a Chief Data & Analytics Officer is crucial, but additional C-suite sponsors who are actively promoting the transformation are also necessary. Furthermore, senior-level supporters must be identified in just about every other function that will be affected by a transformation. If not, these groups are unlikely to evolve their behaviors or commit to a new process. Using the new customer growth example from above, likely sponsors should include marketing, sales, product, customer success and finance, at a minimum. Beyond engaged sponsors, one should expect a majority of the most influential senior leaders to be active supporters (note “most influential” and not a simple majority – this is key). Experience shows that if this is not the case, the road to change will be difficult and lonely.
     
  3. True shared incentives. Shared incentives should come in the form of metrics tied to compensation and annual development goals that start with the appropriate C-level and trickle down to the department. Back to the new customer growth objective: there are several incentives across the C-suite that can ensure this objective is successfully met; for example:
  • Marketing is given a target for cultivating the best net new prospects, which includes applying a tested and governed AI model indicating “most likely to buy” 
  • Sales is given a revenue target for “net new” customers, using the governance-approved definition of customer and new customer, as well as being financially incentivized to focus on this
  • Customer Success is measured by their ability to onboard new customers in the best way possible, leveraging data-driven insights to meet customer needs
  • All of this is enabled through data and analytics, providing the best possible data and predictive models, with consistent definitions, in easy-to-consume formats.
  1. Substantive progress tracking. Appointing a steering committee with executives from different functions is a great step in the process, but simply coming together for monthly check-ins, or receiving status updates on what’s going well and what needs help is not sufficient in itself. These check-ins should be open and honest discussions on where the transformation is making a difference in the “day in the life of” each function affected, as well as where the team needs more business input and involvement. Too often the CDAO is the one driving the agenda, preparing materials for the update to ensure progress is noticed, and feeling defensive when things aren’t going well. If this is viewed truly as a shared transformation with shared accountability and incentives, then progress tracking should be a shared responsibility. Consider rotating the business function responsible for leading monthly updates. 

Specifics make it sticky
I can’t emphasize this enough - without the specifics steps I describe above, change either won’t take hold or won’t stick. Shared incentives are the keys to adoption of a transformation. When executive alignment is missing and shared incentives aren’t defined from the very beginning, the burden for meeting the objectives of a data and AI transformation falls solely on the sponsoring organization or department. And three outcomes typically follow:

  • A lot of money gets burned
  • ROI objectives aren’t met
  • The transformation is deemed a failure

Start smart with your data transformation
Imagine for a moment that you are leading a data and AI transformation that falls directly out of your organization’s strategy, goals and objectives. As Chief Data and Analytics Officer you are the key executive sponsor, but you have other senior sponsors in Sales, Marketing, Product, Finance, and IT who meet regularly as part of a steering committee. 

You also share incentives for the program’s success with the rest of the C-suite. In fact, members of the C-suite have co-authored the incentives, and they don’t include language such as “automation” or “models” or “data governance.” Instead, they use words like “revenue growth,” “customer retention,” and “product development timeframes.” 

This shared incentives “wrapper” is accompanied by a dashboard you use to measure performance and outcomes with your fellow executives. This should be part of the same dashboard that measures the organization’s market share, product, and sales goals. In fact, having shared incentives will make the process of defining, measuring, and operationalizing KPIs a lighter lift than you had imagined. It also creates a sense of shared urgency that makes you feel that your fellow executives will have your back when needed.  

A few more best practices to consider: 

  • Ownership of incentives needs to come from the CEO down. This is where a data leader can make recommendations.
  • The data leader should be facilitating what these shared incentives need to be, with sponsors actively engaged and signing up for their piece.
  • A data leader can do double duty by helping to provide the data to track incentives and outcomes.

When strategy is aligned and incentives are shared, the results can be remarkable. The key to success is ensuring that everyone who can exert influence is not only invited, but incentivized to do so.

It’s simply human nature. People need skin in the game to maximize their motivation for change. The good news is, this formula works whether you’re talking about a data transformation, a new CRM system, or a new marketing tech stack. So if you find yourself brought into a data transformation or similarly large-scale organizational program, start by looking at incentives and how they can be better aligned. 

It’s a little bit like everyone synchronizing their watches.