How To Not Be Stubborn In 2020


I pulled the following two predictions about analytics and decision making from a recent list of 100 predictions by Gartner analysts (subscription required):

  • By 2018, decision optimization will no longer be a niche discipline; it will become a best practice in leading organizations to address a wide range of complex business decisions.
  • Through 2020, over 95% of business leaders will continue to make decisions using intuition, instead of probability distributions, and will significantly underestimate risks as a result.

Apparently most of us will refuse to get the message about optimizing decisions, even after years of tools and best practices being in place. In Gartner’s 2020, we’re all still stubborn foot-draggers.

In my experience, predictions like these often require a grain of salt. Generalizations such as “over 95% of business leaders” at “leading organizations” who “significantly underestimate risk” lack the mathematical precision necessary to inspire confidence and change behavior.

Predictions like this often contain a grain of truth, as well. We frequently prefer our personal comfort zone, resist change, suffer from confirmation bias, and respect the confines of our organization’s formal and informal cultural.

Keep in mind that being stubborn can quickly lead to being history. Accenture CEO Pierre Nanterme notes that half of the companies in the Fortune 500 disappeared between 2000 and 2015. Why? New business models based on digital technologies, including decision optimization. The rapid pace of change and disruption will continue, and increase.

So, how do you avoid becoming a historical footnote by 2020?

  • Start with the end in mind. Decision optimization starts with the BI dashboards that (I hope) you are using today, and extends to advanced analytics that include prediction, simulation, and prescription. Knowing where you’re heading helps you plan a route and schedule for reaching your destination.
  • Start small. You won’t get to optimal decisions immediately. Identifying what decisions you can automate helps you pinpoint feasible projects with measureable ROI. Chances are, regardless of how digital your industry is now, there is low-hanging fruit to be picked.
  • Start now. Start this quarter or this month or this week, or even today. With hosted and cloud solutions, you don’t need to complete a big IT project before you can start improving decision making through analytics. In fact, you don’t have time for the typical enterprise project that requires years.

The year 2020 may seem like a long way off.  In truth, it’s 12 calendar quarters away. That’s not long. Start now and you’ll be 12 quarters ahead of some other stubborn dog.


Improving Your Operations with Data Visualization Applications


Operational and Cost Efficiency

Visual analytics is an effective way to understand the stories in your data and take appropriate actions. Effective data visualizations powered by visual analytics enable you to easily and interactively dive deep into your data to identify opportunities to improve efficiency and productivity, cut costs, and optimize resources; all of which are at the crux of increasing operational efficiency. Hence operations leaders want to quickly understand what is in their data so they can initiate and monitor improvement programs as well as make the best possible decisions for the types of situations they regularly face.

But there’s a small catch – while it’s tempting to believe that putting powerful data visualization authoring software in the hands of business users will result in useful solutions, this is rarely a recipe for success. That’s because creating effective data visualizations requires expertise because visualization authoring software itself does not magically surface insights. Human expertise is required to implement the type of functionality that makes it possible to surface and intuitively convey insights that are actionable for making operational improvements.

Basic tables and charts are easy to create, however solving problems and enabling data discovery that leads to root causes and opportunities to improve operations is an entirely different matter. Spreadsheets and most visualization software make it easy to create pretty charts as well as to combine tables and charts into dashboards but do not fully meet the needs of operations leaders. Let’s face it, if spreadsheets alone were sufficient, you’d have all you need to effectively run your business operations.

Questions that you should ask yourself are:

Do one or more simple visualizations or dashboards containing multiple simple visualizations solve real business operations problems?

Do the visualizations surface buried insights and make them readily comprehensible and actionable?

Is it possible to clearly visualize activity on a map and see changes unfold over time?

Is it possible and to synchronize components within a dashboard to update when data is selected, filtered and sorted?

Of these capabilities, how easily can they be implemented (if at all)?

The answer to these questions exposes the necessity for specific functionality that transcends just data visualizations; application software is required to deliver such functionality, or to be specific – data visualization applications. This is one of the reasons that expertise is required, because applications must be implemented to fully deliver on the promise of visual analytics. Expertise must include art, skill and knowledge that typical operations personnel do not possess. Business users do not understand their organization’s data landscape or how to model and transform their data for visualization. And they often don’t have the time to learn and hone the expertise needed to implement data visualization applications regardless of how simple modern data visualization developments tools are to use.

Full service offerings that use best-of-breed visual analytics are a great way to obtain the needed combination of expertise and visual analytics to enable you to achieve the objective set forth in this post – to improve all aspects of operational efficiency.