“If we have data, let's look at the data. If all we have are opinions, let's go with mine.”
“Everyone fights, no one quits…”
Every company describes itself as “data-driven” but the reality is most companies are only leveraging data to measure half the business. With metrics like conversion, traffic, impressions, fill rates, CPC/CPA, LTV and others spilling out of spreadsheets and fancy data visualizations, the company can tell you how the business is performing but they don’t know much about how their employees are executing. They’re assuming that business performance reflects execution – always dangerous. How can a company be sure they are not leaving anything “on the table”?
To be truly data-driven, companies should be as analytical about internal execution as they are about external performance and their connections. The employee costs alone make it imperative that companies be as “smart” as possible when it comes to assessing internal performance and to do that companies need to set expectations around execution that don’t typically exist. It is not enough to just “get stuff done” but rather how things are done must be viewed as strategic as what things are done.
Otherwise, you put your data team in a tough situation. If the company hasn’t organized operations to be measured effectively (the How), the data team will be of limited value here. I have yet to see a data team empowered to tell department heads how they should operate – it requires a much higher voice and leadership. The only way to win is to change the company and employee mindset. Again, for most companies, employee costs are the largest line-item in the P&L so increasing productivity even ten percent can have outsized impact on the bottomline. However, you can not improve it until you are measuring it.
Gaining insights into operational execution requires all employees to adopt a data-centric mindset that prioritizes measurement and analysis as foundational elements of internal operations. Coupled with the “work quantification” (defined as structuring internal processes to allow for automated measurement), a framework for scaling decision support and building systemic accountability emerges. To achieve this, companies need to broadly adopt data-driven thinking, which is why it’s crucial to embed it into the organizational DNA.
To build an “operational culture” steeped in data-centric thinking, it starts with the culture.
To learn more about data-driven operations or any other topic I’ve written about, connect with me via LinkedIn or set up a call.