The message is clear—we need to become a data-driven organization
Prez just got back from a major consultancy sponsored executive conference where the key takeaway, at least for him, was making your organization a DATA-DRIVEN DECISION-MAKING one. Perhaps to some this seemed like the idea du jour, the currently in fashion idea, but not so for Prez. He had heard all of this before; from his peers, from his advisors, and from his management consultants. It just seemed to be a very complex undertaking, one fraught with risks and uncertainty.
Prez knew it was time to invest in a big data initiative tied to business transformation, but was unsure just how to do it. Being the president and CEO of the company, as well as a major shareholder, he had the power to make it happen. He also had the desire. But how best to approach it without a major corporate disruption? The company was doing very well. The employees seemed happy, and for the most part the shareholders were content. However, he knew this could easily change, especially if the company started losing market share to more in-tune competitors who always seemed to appear.
It was time to make it happen. Just how is the question.
Leadership wants a new direction
Prez gathered the leadership team together and pitched to them this: (from (Stobierski, 2019)
Data-driven decision-making is the process of using data to inform your decision-making process and validate a course of action before committing to it. Today’s largest and most successful organizations use data to their advantage when making high-impact business decisions. How exactly data can be incorporated into the decision-making process will depend on a number of factors, such as your business goals and the types and quality of data you have access to. Though data-driven decision-making has existed in business in one form or another for centuries, it’s a truly modern phenomenon.
Prez challenged his leadership team to:
- Become a data-driven decision-making organization within one year
- Use a modest, time constrained investment that shows immediate value
- Avoid or mitigate risk
- Pull through the organization as quickly, organically, and sustainably as possible
This was not a hard sell for Prez, as Rand in research and development, Sami in sales and marketing, and Fin in corporate finance all have been investigating Data Science, due to having direct reports keenly advocating for this as well.
However, the business department heads were not sure how this would affect or impact their departments. They needed to be convinced.
There is a shown interest within the organization and some pent-up demand as well. The question is, as a company, as Prez has postulated, what is the best approach for all of us?
Mission statement created
After a spirited discussion, leadership hammered out this mission statement:
To steer the company towards a data-driven decision-making operating model that makes highly reliable and validated information accessible to authorized consumers, with data integrity and accountability held and maintained at the most appropriate source. The company strives to be as technology and vendor neutral as possible, maximizing business value while leveraging industry best practices and standards, reducing operating cost while maintaining, or reducing overall headcount.
Now, how to make it happen? This is the 60-million-dollar question.
The Chief Enterprise Architect sees her chance
As the Chief Enterprise Architect, Cea had a seat on the leadership team. The challenge excited her, as her long-stated goal was to steer EA toward a more professional, predictable, value producing practice going forward.
After all, Cea is keenly aware several members of the leadership team aren’t happy with the current enterprise architecture initiative. The results are not up to date or in line with leadership expectations, whatever they might be. Besides, a good EA is EXPENSIVE. What truly is the value of EA? If there is a value, how is it measured?
The Chief EA approached leadership with a proposal: She wants the enterprise architecture team to take leadership on this data-driven initiative.
Leadership green lights the proposal, with conditions attached
Leadership is willing to invest, but only to a point. The team must show immediate, provable value and sustainable progress for subsequent support and investment. Also, leadership is clear—no increase in permanent headcount.
However, before giving the green light, Prez told Cea the EA team must produce a vision statement that clearly and concisely describes the initiative mission in a short paragraph—an elevator pitch as it were.
This is the vision statement Cea came up with and presented to Prez and the leadership team:
Our vision is to help realize the corporate mission statement objective of data-driven decision-making operating model of a sustainable process into the company’s core DNA by using the unique skills of the EA practice and proving, by a Proof of Concept (POC), how this can be accomplished with minimal financial investment, minimum risk, sustainable measured value, little outside expertise, and not increasing EA headcount.
The proposal was accepted and green lit, but only funded for six months. Now it is time for Cea’s team to make it happen. A daunting challenge, but one Cea was willing to take and make happen.
The purpose of these articles and coming attractions
This is the first in a series of articles to clearly identify a usable scenario and a usable proof of concept one could use in their environment.
Not only will there be words to explain the scenario, the approach, and the solution, there will also be usable best practices freely available to use. This is my way of paying it forward, as it were. While the published solution will completely map these articles, it will not completely solve your problem.
These are intended to get you started with the notion of the approach to a data-driven enterprise architecture solution. While I’m providing this information for FREE, this content is just the tip of the iceberg. There will be content, training, and more coming soon I’m excited to share with you.
Watch this space!
(Stobierski, 2019) – Stobierski, Tim, https://online.hbs.edu/blog/post/data-driven-decision-making