With data becoming increasingly available and important to your team’s decision making, there’s more pressure than ever to keep up. New tools, better dashboards, queries—all in the name of working smarter and producing better, more efficient results.
But with all of this data at your disposal, it’s not always easy to identify which information to use and when…or how. At the end of the day, it’s about filtering out the noise and focusing on the KPIs (Key Performance Indicators). But in any given initiative, what are the KPIs and where do you find them? Are they the right ones?
Pro tip: Your first pick at KPIs prior to a new initiative running are often not the ones you end up focusing on once your boots hit the ground. Ongoing refinement is an essential part of the process. Dashboards were meant to be adjusted.
Another key factor: How do you make those data point selections and refinements? And who is doing that all-important data analysis and interpretation?
We’ve seen more teams than we can count create operational data portals using one tool or another, all in the name of deeper insights and more informed strategic planning. However, those “deeper insights” rarely amount to anything more than an overcomplicated dashboard and maybe some slide deck fodder that the rest of the team struggles to understand. Hopefully someone on the team has the gumption to ask the presenter: Is 43% good in that scenario? Do we have any context for that?
You may be wondering why your efforts to make more data-driven decisions don’t always produce the gains you are anticipating (or the gains required by the hefty price tag that many of these data tools and services command.)
NAFSA Update — for those of you attending, Intead sessions to help you move your global enrollment efforts forward:
- Achieving Global Agility: The Flexibility of Global Campus Options
A discussion on the challenges and opportunities of delivering your academic programs at turnkey remote campuses around the world. First-hand experiences will be shared. Tune in: June 4th at 9am EDT
- Going from 0-60: Internationalization
We’ll be talking all things internationalization with David DiMaria, Associate Vice Provost, International Education at University of Maryland, Baltimore County, focusing on how to build leadership buy-in and navigate typically slow-moving internal processes for rapid results. A Tune In Anytime event.
Back to our data discussion...For most organizations, data difficulties begin and end with the lack of a “data culture”, defined by McKinsey & Company in their 2019 Global Survey as “a set of practices that brings together data talent, tools, and decision making so that data become the default support for company operations.”
Sounds simple enough, but in execution, defining, and more importantly, implementing that data-friendly “set of practices” becomes nearly impossible for many teams. Data interpretation skills don't always come naturally to everyone on your team. Data presentation skills are even less common. Decisions on when to use a pie chart vs. a bar chart seem basic enough, but there is a lot more to it if you want the data to inform and motivate your team and impress your leadership.
Read on for three common roadblocks that might be standing in the way of your team’s data approach and what you can do about it.
Roadblock 1: Lack of knowledge at the top
By and large, most department leads seem to lack the necessary knowledge and skills to use data tools. Or maybe they have the expertise but lack the time or the budget to make those tools a priority (and bring the rest of the organization along for the ride).
From McKinsey's 2019 Global Survey on organizations’ usage of data and analytics, the benefits of data-focused leadership were clear: respondents at high-performing organizations were much more likely to report having a data leader in their C-suite, making data and self-service tools accessible to frontline employees, and creating an organizational culture that supported rapid iteration and tolerated failure.
Those departments lacking a data leader, someone knowledgeable and trained in data collection, analysis, and interpretation fall prey to…
Roadblock 2: “Data” consists of self-service, quick turn tools without a long-term vision.
Analytics is about more than just a pretty dashboard — it is about creating tools that are not simply useful in theory but are used in practice. Tools that facilitate a clearly defined end goal that is understood and supported by your team and organization.
And without this end goal, all of your team’s efforts around dashboards and data tools? Well they’re just a complex and expensive means to a nebulous end. And the cause of much employee frustration.
Self-service data tools are among the worst offenders — promising quick insights that are easily accessible by team members across the organization. They rarely seem to work, especially when your team isn’t sure where these tools are meant to take them or how to use them. So much for a “data culture” shortcut, eh?
Roadblock 3: Lack of workforce development, education, and training around data
Unless you are hiring for all positions on your team with data skills as a key qualification, you are likely setting folks up for failure when it comes to data-driven decision making — expecting them to learn and create reports using tools and information that they are not adept at navigating. If your organizational culture is not prepared to support users with the appropriate training at all levels, the expensive “self-service” tools are unlikely to produce the results. You know this. You’ve seen this.
In many cases, even if you have the organizational bandwidth to provide the training, but your team doesn’t really like doing this stuff, they will continue to neglect the data tools due to their overall discomfort. They will give a nod to data in their presentations because they know leadership wants that, but…the term “smoke-screen” comes to mind. For comical insights here please see Sarah Cooper’s iconic “sweet spot” Venn Diagram (among other career advancement gems).
So, about that data-driven decision making, where do you turn?
The Bottom Line
You may be thinking: Revamping my C-suite? Aligning my entire organization on long-term, data-informed strategic priorities? Replacing my staff with a team of data scientists? We agree, each of those solutions is more impractical than the last.
But there’s always another way.
Outside vendors with specialized skills are the most well-equipped to help your team navigate around these roadblocks. A short-term investment for long-term perspective and results by using data to help each department understand how it is doing and what decisions can be data informed.
The goal: achieve better growth and hit those hard-to-reach (stretch) targets.
A qualified external vendor for data support can (and should) provide the technical know-how, training, support when you need it, and most importantly, perspective to inform your strategic goal setting, both short-term and long-term. And maybe even the opportunity to impress the C-suite with analysis and results.
Intead has a long track record of empowering teams through data with short- and longer-term engagements. With us in the technical and strategic weeds, your team is free to focus on taking actions rather than crunching numbers—actions that produce those long sought-after results.
And those results? Well, they speak for themselves. And pave the way forward for the development of that data culture internally, defining that nebulous set of data-friendly practices into clear, repeatable action plans that justify investments in staffing, training, and tools.
When you’re ready to get started, you know where to find us.
