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COOKIE POLICY
Building the strategy is great, but you will need resources and support to execute it. That is where selling the strategy to your c-suite comes in. That said, influencing support of the strategy should have started well before it was built. The best practices from the prior section were developed with the intent of helping influence adoption of the data strategy.
This is the third blog of a three-part series. The first blog outlines why you need a data strategy, and the second blog covers how to build your data strategy. Along the way, I included practical examples you can leverage in crafting and selling your data strategy.
You will need a business case. To get resources and investment to implement the strategy, you will have to show its costs and benefits. Your costs will come in the terms of hardware, software, and resources to build processes and capabilities. They will create both cash and capital expenses. Each company has different rules on how these are treated, and you should engage finance on how to correctly model those outgoing cash flows.
Your plan should create financial benefits. Those may not all occur on day one of the project but occur over time. Again, finance should be able to work with you to model those cash flows, validate your assumptions, and apply the correct discount rates on future cash flows to model the financial return. This will benefit you in two ways:
Example Business Case Summary Slide
You will also have folks who are influenced by a vision of how things will work in the future state. Having the numbers work is great, but they also want to be able to visualize how the future will be different. There are a variety of ways to do this. You can think about how the day-to-day will change for folks in your company. For example, consider how the organization will engage with reports. The example below emphasizes a reduction in the data shovel work to get information, the ability to trust high quality data to make decisions, a more compelling visual presentation of data along with more features like trending, etc. You can use vignettes like this to help people mentally move into that future state and create desire for what it will enable. You may want to enlist your network to create these versus doing them all yourself. It will help them evangelize and feel ownership of the data strategy.
In summary, your influence strategy is to go after the head (business case) and the heart (a better future process or capability that will improve my team’s day to day).
My last piece of advice is to be thoughtful about how you communicate the data strategy and seek approval for investment. I recommend you start by socializing the data strategy with folks close to you asking how it resonates, where it might be problematic, and who might object to it (and why). Genuine engagement and listening on your part are critical here. You do not win by force, coercion, exhaustion – you need support as the roadmap will require a sustained commitment across the organization.
Hit the road with your message and iterate based on feedback until you are ready to ask for investment. Think of your network as circles of influence and start with the closest ones first. This is where you are trying the message, practicing your delivery, and getting feedback on what makes sense and what doesn’t. At this stage, it is critical to listen openly and consider how the feedback can improve both your data strategy and how you explain it. As you refine your message and get more comfortable, you widen your conversation to the next circle of your network. You may go back to some folks a few times to see if your adjustments hit the mark for them.
Eventually you are going to get to all the key decision makers in a one-on-one conversation to get their feedback and attempt to get them on board. You want to be able to walk into the decision-making forum knowing you have support instead of trying to win it from everyone in one meeting. Depending on your company and culture, it may take a few conversations leading to the meeting or many. It is a good bit of work, but it de-risks the final request for support and ensures the strategy you are outlining is on target.
Additional Resources
Reid, SVP of Data and Analytics at UDig, is a long-time data professional with experience at multiple Fortune 500 companies. Most recently, he was the Chief Data and Analytics Officer at Markel. Prior to that he held multiple roles at Capital One including VP of Data Engineering.
