Mastering the Art of Data-Driven Execution: Unleashing the Power within

**Two Parts to Every Analytics Project**

In every analytics project, there are two crucial components that need to be addressed: the technical part and the organizational buy-in. While many focus on the technical aspect, it is the organizational aspect that is the real challenge. Let’s explore why this is the case.

**The Becoming Data Driven Series**

Before delving deeper into the challenges of organizational buy-in, it’s worth mentioning that this article is part of a larger series called “Becoming Data Driven in Business.” If you’re interested in this topic, it’s highly recommended to read the prior parts of the series to get a comprehensive understanding.

**Transitioning from Theory to Practice**

The transition from theory to practice in the “Becoming Data Driven” series involves a crucial step: instrumentation. In simple terms, this means collecting data, establishing a reporting mechanism, and iterating until a causal model of the business is formulated. This process is expected to take a few months.

**The Technical Part: Instrumentation, Data Storage, and Reporting**

Traditionally, discussions around analytics projects tend to focus on the technical aspect. This includes activities such as instrumentation, data storage, and reporting. These are the core foundations that need to be established for any analytics project. The responsibility falls on someone to write the necessary code, set up data pipelines, and create dashboards for reporting purposes.

**The Real Challenge: Getting the Organization on Board**

While the technical part is important, the real challenge lies in getting the organization to utilize the data effectively. This involves helping management gain knowledge and encouraging the organization to embrace data-driven decision-making.

**The Misguided Focus on Technical Best Practices**

Over the years, there has been an overemphasis on technical best practices in the data industry. Data consultants, tool vendors, and thought leaders have often prioritized discussions around instrumentation, storage, and reporting. While these topics are essential, they are relatively straightforward to accomplish with the right expertise and resources.

**The Complexity of Changing Organizational Culture**

Contrary to popular belief, changing organizational culture is far more challenging than the technical aspects of data projects. A data leader once stated that there are only two ways to make a company more metrics-driven: either the CEO leads the change from the top down or every non-data-driven leader is removed from the company.

**Illustrating the Difficulty of Changing Organizational Culture**

To illustrate the difficulty of changing organizational culture, let’s take a look at a story involving Alan Mullaly and Ford. When Mullaly was considering joining Ford, he held a secret meeting with board members John Thornton and Irv Hockaday. They discussed the challenges of navigating the internal politics at Ford.

**Enforcing Extreme Accountability**

During the conversation, Mullaly outlined his system of weekly meetings that enforced extreme accountability. This approach left no room for anyone who wasn’t fully committed to executing the business plan. Mullaly believed that many people at Ford would ultimately self-select out due to the new level of accountability.


In summary, every analytics project consists of two parts: the technical aspect and the organizational buy-in. While the technical part is essential, the real challenge lies in creating a data-driven culture within the organization. This requires leadership involvement and a commitment to change. Changing organizational culture is far more complex than implementing technical solutions, and it is crucial to address both aspects to achieve success in analytics projects.

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