When you hear someone talking about the Analytical Maturity of an organization – what does that mean? IBM has put together a handy “temperature reader” for this called the Analytics Quotient Quiz. It can give you an idea where your organization lands on the spectrum. Are you a Novice or a Master? If you’re reading this post, I’m guessing you’re somewhere in between, or at least curious about where to start.
IBM research also indicates that Analytics-driven organizations outperform their peers by up to 3 times. The same research also shows that analytically mature companies have an Analytics Center of Excellence.
“That’s great, IBM, but who the heck has time to build a Center of Excellence? I’ve got a business to run here!”
Some shy away from implementing Analytics because it looms “out there” as a huge implementation that’s expensive and time consuming, especially if your standards for project management adhere strictly to the Waterfall methodology.
Incorporating Analytics into business processes does NOT have to be a huge implementation across the entire organization. In fact, most companies that start small with one project in one department routinely see more ROI in less time than those who opt to do a large enterprise-wide implementation (where it’s easy to overspend on software and man hours, even if you’re getting a heck of a deal). Sometimes that first Analytics project is as simple as automating repetitive reporting processes such as data gathering, merging and cleansing. A “starter” project like this frees up analysts’ time to do real analysis. You know, the kind that uncovers the big ‘ah-ha’ moments…the kind they make TV commercials about?
As a frame of reference – most “starter” projects are linked to one of these four initiatives:
- Grow, retain, and satisfy customers (students, citizens, parents, policy holders, etc.)
- Increase operational efficiency
- Transform financial processes
- Manage risk, fraud and regulatory compliance
As a result of success realized with these “starter” projects, other analytics projects become obvious as next steps. It makes sense to then prioritize these projects, and expand the overall analytics program (training, hardware, software, staffing, etc.) as it’s appropriate for other initiatives, business problems, departments, lines of business, etc. This is more aligned with the Agile project management methodology (in comparison to Waterfall methodology), and is generally more palatable from a timing and budgeting perspective. It is much easier to budget annually for controlled growth of analytics across an organization than it is to budget for a huge multi-million dollar enterprise project – for most companies, anyway.
Before you know it, many of these analytics projects are approaching maturity and automated stages, and that organization is stepping right on up through the ranks of Analytical Maturity:
- Making more data-backed decisions
- Reducing fraud, waste and abuse
- Customer Satisfaction on the rise
- Customer Churn is falling
- Customer base and wallet share are growing
This concept of Analytical Maturity is really to say that Analytics (like many other things in life) is a journey, and not a destination. The best part is, an organization can leverage the learning curve as they go along, gaining analytical prowess and expertise at each step of the way. More often than not, the folks who act as Change Agents in promoting transformation into the analytics driven age within their organization see resounding success and career growth, alongside the obvious benefits to their organization.
Among all of the marketing around BIG Big Data projects ($$$) – it should also be quietly implied that it’s a good idea to start small, maybe with the intention that more data-backed decision making in more areas of the company over time will grow the organization into an Analytically Mature company.
In your market – can you recommend a good place to start with an analytics project?
Are your analytics projects helping you outperform your peers by 3X? If not – we should talk…