Whether you lead a team, division, or department, decisions about what to start, stop, or continue doing should be driven by something more than a “gut feeling.” Decisions based on evidence, including the right data (and the right interpretation of that data) will always outperform intuition over the long haul. However, this maxim comes with a caveat!
Data-driven decision-making and access to information are vital to success, but not all data or information is valuable. Effective leaders know how to sift, sort, and ensure that what matters most is what gets measured. Data collection is necessary, but not sufficient. It is the interpretation of data and the strategic sharing and utilization of the information to drive future success (or the elimination of failure) that matters most.
As a senior leader in a large publicly funded organization with a near-billion dollar a year budget, it was imperative that decisions were rationalized, measured, and evaluated on the basis of data. I feel great satisfaction knowing that many of our decisions were responsible, strategic, informed by data and ultimately impactful.
Decisions about what to start, stop, or continue doing should be driven by something more than a “gut feeling.”
Equally true, I am embarrassed by the number of times politics, pet projects, or “spin” won the day over thoughtful, objective analysis of data held up to the light of a strategic plan. We also occasionally collected data without knowing why – expending precious resources on the useless task of generating data so that we could forward it down the pipeline to some anonymous abyss.
How do we decipher the difference between helpful and unhelpful data?
DATA is HELPFUL:
1. When it drives mission critical action.
Highly effective organizations have articulated a clear and compelling vision/mission that defines their reason for existence, determines priorities, and drives core actions. Data collection can be an important catalyst in converting declared intention into actual activity that supports goal attainment.
2. When it provides a motivating picture of success.
Organizations that are focused, progressive, and serious about accomplishing goals that serve their mission want to know if they are winning or losing. At the end of the day, it is motivating to know that strategy, capacity, and effort have combined to move the organization forward in the effort to fulfill their purpose.
3. When it provides timely feedback to support learning.
Great organizations are passionate about continuous improvement and know how to learn and respond in real time. Foundational to learning is the capacity to diagnose needs and problems, correct counterproductive efforts, and reinforce best practices. None of this is possible without the strategic collection, interpretation, and communication of data.
4. When it serves to support an accountability framework.
In most organizations, it is the capacity of individuals to function as contributing members of an aligned and connected whole that makes the difference between failure and success. Strategic, intentional, and consistent collection and reference to data can serve as a vital part of the connective tissue that holds great organizations together and drives them forward in a coordinated, sustainable manner.
DATA is UNHELPFUL:
1. When it comes too late.
While collecting after-the-fact data in hindsight (aka “lag data”) can be helpful in knowing whether or not an initiative was successful or not, it isn’t helpful in making mid-course corrections or improvements. Collecting on-the-fly data (aka “lead data”) to support effective execution of a plan is just as important as measuring overall success. Great coaches don’t wait until the end of the game to impact outcomes, reinforce success, or bench underperformers.
2. When it lacks purpose.
Raise your hand if you have ever had a “higher up” ask you to collect data at great inconvenience and expenditure of scarce resources, only to send it along and never have any idea whether it was used or referenced by anyone. Was that a motivating experience? Enough said!
3. When it clouds instead of clarifies judgement.
The word obfuscate was created for exactly this situation. Synonyms include mystify, complicate, befuddle, confuse, and obscure. That is precisely what happens when strategic collection and data analysis aren’t married to a thoughtful plan for distilling and communicating the essence and implication of the data. Too much data that requires an archaeological dig before sense emerges isn’t helpful.
4.When its reliability, integrity, or interpretation are called into question.
Attention to the ethics and science of data collection shouldn’t be an afterthought. Neither should issues of resource deployment, storage, and reporting. Allegations of mishandling, breeches of confidentiality, sloppy analysis, or doubts about how data will be used are a recipe for mistrust and cries of “fake data.” Good intentions and the little checkmark beside the “collect data” box of your to-do list won’t undo the damage.
Start small. Aim for a single, key problem or an important (but limited) area of the business where predictive, diagnostic, or summative data analysis can have a valuable and immediate impact. Then build a data collection strategy that will support effective use of the results to build credibility, excitement, and momentum. Build on one experience to replicate good data collection, analysis, and communication practices into the DNA of your organization.
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