Business Intelligence and Data Analytics

July 16, 2020
Dray McFarlane
Business Intelligence and Data Analytics

What are organizations typically talking about when they discuss business intelligence? In my experience, they're generally referring to some way of reviewing and summarizing what they have collected - in various forms including databases, spreadsheets, and whatever else they use to track information - so people can readily understand what is. This is great! You can use this to help figure out what's happening right now, what you might need to pay more attention to, and even leverage it for some forecasting. Even without all that, I know I generally feel a warm glow as a really complex set of data produces a simple, easy to understand, and hopefully colorful chart.

However, when you start talking about what actions will be most effective in the future, this typical approach to business intelligence tends to require... creative interpretation. You can eyeball a good chart and - based on intuition, experience, third party consultants, or talking to a local fortune teller - declare what your priorities need to be to move that chart in a more positive direction the next time it gets run. But what do you do when you're dealing with so much complexity it's hard to get a good visual? What about finding gold in your data beyond what your experience plus instincts can determine?

Ultimately, BI is good at forecasting when expectations are pretty simple and general in nature. You probably expect meeting registration numbers to look pretty similar this year when compared to last year. You can even guess what the impact of major events might be and build that in, too! But are you able to answer really specific questions? Does an increase in e-learning consumption lead to a reduction for in-person meeting attendance? Are people more likely to renew if their renewal date falls near a particular deadline or event? Does that answer change based on another or even many other criteria? Your data knows, but working with tools that are designed to tell you what is means you're going to have some work left to do after that initial rush of seeing those pretty charts and graphs has faded.

Good news, though! There are plenty of methods to take your information to that next step. Instead of just describing, all that information you've been working so hard to collect and keep clean can start doing the predictive work for you. Even beyond that, with those predictions it can start calling out patterns in a way that help guide you towards a more effective approach to serving your constituents whether that means getting better content in their hands, better access to their existing benefits, or identifying those who are likely to sever their connections to you so you can work closely with them on an individual basis.

Data analytics can leverage powerful, statistically proven models to help with this and more - maybe the biggest benefit is finding things you never would have looked for! Various approaches to optimization, forecasting, and clustering can be easy to implement and provide benefits very quickly, but then you can expand further into more complex areas that allow machine learning to do its thing and report back on details that can be nearly impossible to tease out yourself.

These topics can definitely feel intimidating if you don't have any background with data analytics but we at Tasio are here to help! We will work with your organizations to get all of your data together (and possibly bring in some external sources where they're useful) and run them through these models. The results will show us not just the business intelligence of what is, but also why and what we can expect next. From there, we will engage with your business users to identify concrete actions they can take to impact those outcomes, making sure to allocate limited resources like time and money where they will be most effective in furthering your missions.

Dray McFarlane

Follow us on social media