The All Too Common Pain Points of a Data Leader

It’s often the case that the more I learn, the more I realize that I habitually underestimate the knowledge I’ve already gained.

Glass half full…your data problems are probably similar to everyone’s data problems

I recently decided to invest in and place a bet on myself. At the risk of sucking the time and money out of my first few post-vaccination months, I decided to enroll in the Chief Data Officer program at Carnegie Mellon. I did so for a couple of reasons. First off, it’s an amazing opportunity to learn from experienced and accomplished experts. These current, past, and aspiring CDataOs are my role models, and the opportunity to get closer to them holds tremendous value. Secondly, I wanted to calibrate my own experiences in Data leadership with the experiences of my peers. What I’ve found thus far is that many of my “data problems” are ubiquitous, regardless of industry, size of org, or other variables.

So if you’re like me, and you’re fortunate enough to find yourself in a position of influence and responsibility for much, if not all, of the Data-related prospects of an organization, then I can almost guarantee some of the experiences you will have. For unless you are the exception to the rule, you will undoubtedly recognize and experience the frustrations associated with the following opportunities for data and analytics maturation.

Lack of an org-wide Data strategy:
* Disjointed and fragmented approaches to value creation from Data assets
* Misaligned goals associated with Data & Analytics
* Lack of single point of accountability for the success of Data-related efforts

Shortage of Data & Analytics skills:
* It is difficult to find & retain talented Data Engineers, Data Scientists, Analytics Engineers, etc
* That relatively small pool of talent makes it difficult to “democratize” analytics insights in an organization
* The growth of an organization will inherently narrow each practitioner’s scope of work — consequently, making it difficult to maintain a clear sense of who owns which part of an organization’s Data supply chain
* On a positive note, Data & Analytics technologies are improving quickly, which is making it easier (i.e., more predictable) for Data leaders to target the right gaps to hire/retain talented practitioners

Lack of C-level influence and/or sponsorship:
* Perhaps the most important skill for a Data leader to possess is being able to communicate with all levels of the organization
* There is always more demand than supply of Data resources; thus, it is vital that a Data leader partners with C-level executives to understand what is MOST important
* C-level executives are under pressure to produce results, and therefore Data leaders consistently feel that downward pressure

Poor data quality:
* Analysts and Data Scientists spend too much time cleaning their data before they create an output
* Lack of trust in data is crippling for organizational process and structure
* Poor data quality slows operations and production
* It creates a context where blame is placed on everyone…and by everyone
* Without proper management of data at the source, it becomes much more difficult to create consistency and accuracy of insights from your data

Siloed & slow data
* Results in difficulties identifying “sources of truth” for business critical insights & KPIs
* Specifically from a Marketing and User Experience perspective, the longer the time between Data Creation and Data Availability, the less value you can create from your data
* “Real time” internal analytics are generally much less important than “real time” customer activation and experience strategies

I will follow up this post with prescriptions and strategies that attempt to address some of the above issues. Until then…

post written by Bill Saltmarsh

Bill Saltmarsh is the Head of Data at Pluralsight — I’m a truth-seeking optimist stuck at my desk. I’d rather be exploring & enjoying the outdoors.