By Bobby Holmes
Starting the analytics journey
Our digital universe is creating data at a rate that even Moore’s Law struggles to explain. As technology continues to evolve and more people gain access to it, our world of connectivity will produce a mind-boggling number of data points every second. The logical question often asked by organizations is: “How do I use this data to gain a competitive edge?” Analytics is no doubt one of the hottest topics in the marketplace — and for good reason. Personally, I have been fascinated with numbers my entire life, and have continued that passion into my career. I’ve helped organizations with advanced modeling point solutions all the way to designing their entire analytics program, including technology architecture, operating model, and change management initiatives.
In my years of experience in this space, I’ve seen well-established analytics functions and dysfunctional ones. More often than not, it’s the latter. Companies buy stacks of technology in the hopes of out-of-the-box solutions providing groundbreaking insights. The reality is that technology is only an enabler, and without the right strategy and operating model surrounding the technology, all you have is a very fancy (and likely expensive) piece of software that isn’t fully utilized. So where should you start? Whether you’ve already begun your analytics journey or your organization is brand new to this capability, the starting point is similar.
Establishing the vision
This may sound cliche from a consultant, but every function or initiative in an organization must have a vision. For analytics, it is a deliberate strategy to expose data to answer your organization’s most critical issues. (You’d be surprised by how many companies cannot articulate this.) A powerful tool we use at Appirio is a VisionMap — a collaborative exercise that outlines the analytics direction with clarity and alignment, and targets for accountability. Being able to clearly and confidently communicate this to your key stakeholder population is critical for future funding and change management. It’s also a constant reinforcement mechanism as you execute your roadmap.
Identifying business value
Equally as important as establishing your vision is understanding the true business needs of your data consumers. This should not be defined in the vacuum of a corporate design session, but rather in the field with your leaders. Go out and talk to the business to understand what data they are using every day and how they gather that information. Understanding the voice of the customer is critical to program effectiveness and adoption. They likely already have a pretty good idea of what type of information they need to manage their teams and products, but oftentimes they run into capacity or technology limitations, creating roadblocks to connecting their information.
Also, if the data they need is not something you already have, then that’s additional information to plot on your roadmap of data capture. Making their job easier with quicker decision-making is the foundation of analytic maturity. They will also likely have some lofty wants that relate to predictive outputs which are to be noted for future development as your function matures, but being able to deliver real business value early in your program is critical — even if it’s as simple as saving them 30 minutes each day, generating multiple reports for elementary information. Start small and deliver targeted information that is relevant to your consumers.
Personalizing the experience
All transformation initiatives revolve around pushing information and action to the user when they need it. Self-service is a fantastic capability when it’s actually used. Too often, I find the analytics function pushing more information (mostly reporting) to the consumer that can easily be executed through self-service. To increase self-service adoption, the analytics team must fully understand the different consumer personas that exist in their organization. An executive will have different needs than a manager, so one set of service delivery processes and outputs will not yield the desired benefit.
At Appirio, we use journey mapping to identify these key transaction points to understand — based on persona type — when a consumer will require the information, how they will use it, what decisions can be made, and a feedback loop for constant improvement. In today’s world, a consumer-based experience is required by the workforce. They should be able to access their information at any time and on any device with similar functionality. The challenge here is defining what information each persona group will need at any given time, which is an output of a successful journey map. As all of us should know, accessibility to information does not mean adoption. It needs to be a personalized experience for each consumer group of data.
Tying it all together
There are many variables that go into standing up or expanding any organizational function. What I’ve laid out above are table stakes, but are fundamental for an analytics function to thrive. It’s important to note that you never once read anything about analytics technology (e.g., business intelligence) — other than assuming you have core system functionality — that contains self-service. After completing the vision, talking with the business stakeholders, and mapping their experience, requirements will emerge that will provide valuable input into your analytics technology needs. This sequence of events will ensure that you’re putting the consumer at the heart of your analytics journey — which will ultimately lead to greater business value.