3 Analytics Fears…And How To Beat Them!Posted: July 15, 2014
People often have fears, real or perceived, that if not addressed properly can adversely impact the successful implementation of any business transformation. Analytics is no different. Effective change management is a critical component of any Analytics Strategy.
Consider the three fears below recently shared with me and approaches to mitigate them:
- “Analytics won’t produce an answer.” – While this is a viable outcome, it should not be a fear or concern. If the best data scientists analyze the most relevant data with the best tools and methods available…and don’t identify a pattern in the data…that is your answer! The answer may be that the data won’t help – there is no pattern. Your best course of action is to use your instinct and experience. But at least you’ve explored whether the data could help and have ruled that out as a possibility. And you’ll be making a better decision!
- “They won’t tell us that they cannot find an answer.” – This concern goes something like this: the data scientist won’t find a pattern, but in order to justify their rate/job/existence, they’ll fabricate an answer. And while some disreputable analysts might exist, the majority are reputable, inquisitive and curious by nature with a huge appetite to find an answer. They’ll keep digging and analyzing as long as you allow. And when you call it off, they’ll let you know that no pattern was found. So check the references on your hires, be sure you can trust them. Then let them at the data, and be comfortable that they won’t fabricate the result.
- “We’ll think we are smarter than the data and we won’t listen.” – This fear simply comes down to leadership and culture. Does your organization have top down senior level advocacy of a data-driven decision-making culture? And will they hold others accountable? If yes, then this fear is rather easily managed by evaluating your decision making performance. If specific individuals “don’t listen”, consistently decide against the recommendation of the data, and turn out to be wrong, then leadership must hold them accountable. On the other hand, if they turn out to be right most of the time, make sure that you adjust your models, data sets or methods.
Are these fears common in your organization? Likely.
Are there others? Likely.
Find out. Talk to key business leaders and partners, especially those resistant to analytics. Ask them and take time to understand their concerns. Then go about resolving them. Only after ensuring that the people aspect of an analytics initiative is address, can you effectively implement the process and technology changes necessary to implement the strategy.