With all the data in the world today, where do you find the balance between action and insight, creativity and accountability, art and science?
At a recent client, managers grew furious with a system whose new analytics effectively held them accountable for bottom line accounting results they thought undermined their key account relationships. The sophisticated and near-real-time analytics created the worst of both worlds for them: greater accountability with less flexibility and influence. The struggle we face is humanizing the results of big data sets – and combining the science (data) and art (experience) to produce REAL goals and targets. How do you know what data to use, and what result to measure?
In a simple real life example, who is the bigger star: Usher or Justin Timberlake? If we just used data without context we may get varying answers to this very open ended question. When we apply reasoning, objectivity and understanding we first get the right QUESTION, then we can go get the right data set. Businesses are doing the very same thing: holding people accountable to poorly constructed questions, resulting in incorrect insight and action. For the sake of our example, let’s assume we are asking: who makes the most money? The tendency would be to compare Usher’s and Timberlake’s music careers. It’s a good start, and the ecosystem of data would be statistically sound to believe it’s a fair comparison and a good yardstick to measure their success. However, when we add insight, we realize Timberlake has royalties from N*Sync, a movie career, television appearances, endorsement deals and his own Sauza tequila product. Usher is a very successful entrepreneur too. Knowing that both have careers outside of music, how would you rephrase the question? Having the insight to ask not just the right question, but ask it correctly – is the FIRST principle of strong accountability.
Now back to your business… are you asking open ended questions and hoping your data can justify the answers? Or have you taken the time to find out when, how, why and what generates the success of your business. The “intelligence” people aspire for in using data is not in the data itself, it’s in the application and understanding of the data which creates the magic. Business Intelligence has become such an overused term that it tops the list of most hated terms in business in 2016. Realize it’s not the business or data that creates knowledge, it’s the people asking the right questions, and applying the right data sets to find the right answers. People still come first in a world of data.