We are bombarded by big data, data visualization, and infographics. In attempting to join in, a common mistake when starting to use data in program evaluation or other organization measures, is to collect data that is easy to gather and measure. However, this often misses the so what; i.e., what does the data tell us about how we’re doing.
Beth Kanter in Big Data Without Defining Success First is a Big Mistake on September 28, 2012 clearly states,
But I think jumping into a process: ”Gather, Analyze, and Act” without defining success (or failure) on the front end might lead to wasted time.
Kanter provides an example from DoSomething.org. For many nonprofits the most difficult step, yet the keystone, is describing what success looks like. However, this article does not specifically address this key step.
To Succeed with Big Data, Start Small by Bill Franks on October 3, 2012 on the HBR Blog Network
While it isn’t hard to argue the value of analyzing big data, it is intimidating to figure out what to do first. There are many unknowns when working with data that your organization has never used before — the streams of unstructured information from the web, for example. Which elements of the data hold value? What are the most important metrics the data can generate? What quality issues exist? As a result of these unknowns, the costs and time required to achieve success can be hard to estimate.
Franks’ advice is to start with simple “analytics that don’t take much time or data to run.”
Pursuing big data with small, targeted steps can actually be the fastest, least expensive, and most effective way to go. It enables an organization to prove there’s value in major investment before making it and to understand better how to make a big data program pay off for the long term.
His advice is useful, if the organization has completed the critical step of defining success. That is, once the organization can describe what success looks like, the next step is to determine how success can be measured. I recommend than applying Franks’ advice to begin with small steps to develop metrics.
Robert Plant in Big Data Doesn’t Work If You Ignore the Small Things that Matter on the HBR Blog Network on October 5, 2012, states,
Big data is today’s panacea, the great new hope for unlocking the mysteries of marketing. To avoid being left behind, companies are rushing to cash in on the information they glean from customers, and vendors are stepping up to help.
Companies would do better at satisfying and retaining customers if they spent less time worrying about big data and more timemaking good use of “small data” — already-available information from simple technology solutions — to become more flexible, informative, and helpful.
And in the frenzy to capitalize on big data, don’t forget what it’s like to be a data point — an individual customer dealing with your company. If you’re not making your data points happy, they’ll gladly move into someone else’s database, just as you did after the repair service failed to show up.
I agree, to measure success, review appropriate data. When investing in a stock, for example, the trick is to choose the important criteria out the the scads of data they publish.
But also with stocks…luck….as in “I would rather have a lucky general than a smart one.” but I digress.
Thank you, Joann. Seems that as an investor there would be so many other factors in addition to the data the company offers.
Perhaps there may be a blog post one day about lucky generals and smart generals.