The number one reason your enterprise analytics is doomed to failure

By Anthony STAGG posted 09-08-2016 05:53 PM


A young, very bright and hard-working digital analyst on my team came to me many years ago in the middle of a reporting project, put her hands up in the air, and in abject frustration blurted out “ Why does everything we do have to be so hard?”    After explaining the problems she had been having pulling data from a digital analytics platform for the last 2 days and not getting much timely help from the vendor’s tech support team, then after finally downloading the data, attempting to join, clean, standardize, and dedupe  this data set with several other data sets from other digital marketing platforms using Excel(this is before  the recent slate of new data prep and data integration offerings from software vendors) , she was now  running up against a deadline, and struggling to come up with many meaningful insights, other than trite and obvious observations.  She explained that of the 20 hours she’d spent on the project so far, 16 hours had been spent attempting to pull, join, and prep data to get to a point where she could, actually, run analysis.  .  (Data prep and data integration using Excel from multiple spreadsheets is time-consuming, and tedious work, and prone to human error, if you’ve ever done it, and I have).


Her next project was to figure out how to automate Excel reporting using SQL and APIs for a monthly dashboard consisting of multiple tabbed worksheets versus the unwieldy manual process we had been using.  There were several other projects on her schedule all with tight timelines requiring a prodigious amount of technical, technology, and mathematical competency using different analytical, campaign management, content management, search marketing tools, etc., not to mention understanding the online marketing channels under analysis, and having some insight in to the human behavior within these channels, so she could provide strategic recommendations to the client.  

All in a typical digital analyst’s week you say?  May be, maybe not.  Either way, I believe that the scenario described above is fairly representative of the work most digital analysts are doing.  The fact that we have more analytical and marketing tech tools and platforms available to us now should be making our lives easier, and making us more productive, but they’re not—or, at least, not to the extent they should be.   You’re all familiar with the research studies that show that analysts are spending up to 80% of their time on data prep and data integration, and only 20%, if less of their time on analysis and actually developing insight is just one indication, but not the only one, that we’re not delivering the value we could be to the business.

 Much of the problem, in my opinion, is the result of the way digital analytics as a function is organized and managed.  Very, very few businesses have a formalized vision and strategic plan for the development and management of data and analytics capabilities.  Notice I used the term “data and analytics capabilities”, and not digital data and analytics capabilities.  Without a formalized vision and strategic plan that addresses the development of all marketing data and analytics within an organization—both online and offline marketing—the digital analytics component won’t function at its highest level, since the line between both is rapidly disappearing in an omni-channel environment.   In order for an organization’s analytics capabilities to advance to a higher level of maturity, all 3 pillars of analytics enablement—tools and technology, human development, and process management (the operational procedures for how analytic solutions are delivered) be addressed—and all three must be developed simultaneously, if possible.   If there is no training and development plan in place for the analytics department, analysts won’t advance their level of technical, analytical, and management skills, and the evolution of the organization’s analytics capabilities will be compromised as a consequence.  All the tools and technology in the world aren’t going to change this—in fact, they will cause organizational disruption and chaos in the short term.

Addressing only the tools and technology piece results in an incomplete and ineffective approach that fails to deliver full value, which is where most organizations are today.  A lot more thought needs to be put in to the human development aspect –aren’t we asking too much of digital analysts?, shouldn’t the function of digital analytics recognize the need for different roles, such as analytics architect, data strategist, data analyst, data visualizer, analytics implementer, etc., rather than expecting one person to be proficient in all these areas? 

We expect an architect to draw up architectural plans and know something about electrical work, plumbing, cabinet making, dry walling, and building codes and everything else to do with building a house, but we don’t expect him/her to actually do the installation work.  Taking a similar medical analogy, we don’t expect our doctor to run the front desk, take our vital signs, do lab work, injections, take X-Rays, MRIs, etc., all of which require proficiency with different tools, etc., yet , far too often, organizations expect digital analysts to be programmers and developers, data visualizers, experts in running SQL queries, proficient with many different data, analytics, and digital  marketing tech platforms, expert modelers, advanced in Excel, proficient with B.I. platforms, skilled in providing strategic insight, and loaded with an intuitive grasp of human behavior.  A few—very few—will measure up, but the result is usually a jack of all trades, master of none situation.

 The young analyst I mentioned earlier eventually left our company, and went back to being a financial analyst with a retail bank where she was able to earn more, focus her energy on just a handful of data and analytic tools, and enjoy a bit more sanity in her working week.  I believe it’s time for a radical and comprehensive re-think of how we’re managing and developing the marketing analytics function.  This starts with a clearly defined, comprehensive, and actionable planning and implementation process—see Fig A below—Analytics Capabilities Development Process.  In essence, this is strategic planning for marketing analytics.


Fig A



At each phase of the process, specific data inputs and outputs are required to facilitate decision-making and strategic direction, which will vary for every organization.  The process must address equally all 3 pillars of data and analytics enablement:  Tools and technology, human development, and process management.

The pace of technology innovation, the torrents of data, and the demands of business owners for faster and more meaningful insight are unlikely to slow down anytime soon.  We desperately need to bring order, clarity, and focus to the marketing analytics function, if we are to avoid these pressures from overwhelming us.  The sooner we start doing something about strategic planning for marketing analytics, the better chance we’ll have of preventing promising young analytics talent like the one I mentioned earlier from exiting the industry.

Until supply meets demand, many organizations will continue to find it difficult to attract and retain the talent they need to build competitive advantage. In fact, four in ten survey respondents report difficulty attracting people with analytical skills, and an equal percent struggle to retain them. Surprisingly, many companies have yet to develop an effective talent strategy; they are not doing anything different to attract new data workers. Only one in five organizations has changed its approach to attracting and retaining analytics talent.


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