The tragedy of free floating data

We’re getting exceptionally good at grabbing metrics from anywhere, and in real time, too. Business intelligence tools have evolved into visualization apps and as a result, colors, shapes and lines tell us whether we should be happy or unhappy about data. We are awash in ‘cues’ from inside and outside our enterprise. But by itself, more data and better visualization aren’t the answers to better business outcomes; they are just free-floating data.

Getting to the reward

Cues are only as good as the behaviors they stimulate in response. Without paying close attention to the behaviors, which we call business processes, we end up with a ‘fog’ of activity that isn’t repeatable, isn’t accountable and is unlikely to gain the reward (which can be avoiding a disaster or increasing revenue) that the cue signaled. Worse, we can’t be sure activities that should cross functional boundaries are doing just that. This is the tragedy that befalls most organizations.


Beyond a response, processes form the context for metrics. Organizations that haven’t modeled their enterprise may have the greatest dashboards but lack an ability to know how and where to make change when data shows a problem or offers an opportunity. Cues are wasted when they aren’t understood or framed properly. “That’s the way its always been done around here” is a great answer when there’s no better explanation for why and when we respond to a cue.

Best-selling author Charles Duhigg talks about the management of responses to cues in his bestseller, The Power of Habit. The cookie story is a great analogy for not understanding the context of a metric, poor organizational response and an undesired business outcome. His message is simple but powerful: Understand the cue, be deliberate in response, and gain the most favorable outcome.

Continuous improvement

Once we’ve figured out when and why we measure, we need to understand what to do when data tells us to act. We need to be constantly looking for better ways to respond and make the reward more consistent and larger. We need ways to know that each member of the organization is aligned with what cues mean, what activities cues prompt, and what outcome we’re expecting. That requires either an enormous amount of labor or automation tools that can make the effort manageable.

Going beyond data

At some point, enough cues have been analyzed, put in proper context in a business model and outcomes sufficiently optimized that the organization reaches a higher level of sophistication. Better and more meaningful cues are developed, targeting more specific opportunities, resulting in an ability to manage complex events with complex responses. The most sophisticated organizations have created a platform for a cycle of analysis, correction and organizational change. It is a virtuous cycle that only starts with data but ends with predictable reward.

What are your thoughts on the tragedy of free-floating data?


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Categories: Data Analytics / Big Data, Disciplines, Featured, Future of work, Process Management

Author:Tom Molyneux

A business process strategist with a focus on real-time event management.

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10 Comments on “The tragedy of free floating data”

  1. April 24, 2012 at 10:18 pm #

    You grabbed my attention and pulled me into reading to the finish. So, data is OK to start with but look for rewards…. is that the message? Is there a way of targetting REWARDS and working out means to getting them? That is not what is clear. Have I missed something?

    • April 24, 2012 at 10:27 pm #

      Putchavn, thanks for the comment and thanks for reading to the end. The message is that data is very powerful and can be used to provide meaningful cues that something needs to be done. However, to round this out and provide real value, the cues should be linked to some best course of action (a process).

      Once this link cue –> action is made, then it’s possible to start looking at outcomes and what are the best actions for particular cues.

    • April 25, 2012 at 6:26 am #

      Putchavn, this problem exists with data (where we think better dashboards will solve process, but is the same issue with social media. We want people to collaborate, but around what? I have a theory that data becomes a bright, shiny object for organizations, as does social media. People aren’t thinking ahead to, “OK, now what?”

      • April 25, 2012 at 7:34 am #

        Chris: Perhaps that is so for the cases you have studied but with very elaborate formalization and periodic auditing of Purpose, Vision, Mission, Objectives, Quality and other Policies, Business Rules and Business Management / Quality Management Systems, I cannot believe that corporations, that too Business Enterprises create data and get lost. Ironically I do not have DATA for my disbelief!!!

        So, is the case with social media. Many people may sign up and NOT know what to do next but NOT ALL. I get invitations for Networking and I thank them for the invitation and ask “what shall we do together?”
        Very often I get specific requests / proposals and we get on with some useful interaction at times leading to professional engagement. That is good enough though more is welcome from those interested.

  2. Ron Webb
    April 25, 2012 at 8:43 am #

    Great article and very much aligned with the experiences we have here at APQC. As you are probably aware, we’ve developed process framework to try and help solve this, among other, problems.
    We developed it for this very reason. There was not a common language for organizations to understand their processes or compare their processes with other organizations.
    Once you get past the huge task of data definition (what is included in “technology costs”), you have to take on the task of defining the processes and activities that you are examining in order to give your data context.
    One of my favorite exercises these days is to ask audience members to determine where they measure revenue in their organization. Some say it happens when it is sold, others say when we are able to realize it in our financials, while still others say revenue is only defined when the customer pays for it. Those are all very different processes
    Another example is cost data. If you have cost data, you have to know the starting point and ending point of the process that is reflected in that cost data. In healthcare, do you define the cost of birthing a baby at the end of delivery, recovery, or postpartum care? A measure of the total cost of birthing a baby has no real meaning unless you know the specific activities that are encompassed in that data.
    That is why our members asked us to develop our process classification framework and one of the many ways it is used. Our members benchmark their key organizational processes using this framework and are able to have a clear understanding of their own organization, but more importantly, they can then compare themselves to other companies that have adopted the same process framework.
    In a system like this, the “total cost of the finance function per $1,000 of organizational revenue” means the same, regardless of organizational size, industry, or geography because the process and definitions are clear and consistently applied.

    That is the real power of big data.

    • April 25, 2012 at 8:54 am #

      Excellent point and an add-on to the article…if you don’t know what to attach data to process-wise, how in the world can you compare your reward to the reward others are getting?

    • April 25, 2012 at 9:45 am #

      Ron, thanks for the post. I couldn’t agree more. Having an agreed upon framework like the APQC PCF with pre-defined metrics really helps provide context and meaning to data. It also yields a common understanding when benchmarking.

  3. April 25, 2012 at 8:43 am #

    I see the issue of floating data through a process and measurement lens — noticing that measures are not on target is useless unless you have a way to change the work that drives the performance. At Toyota, this would be problem solving, and might involve “strategy deployment”, also known as Hoshin Kanri, which translates objectives into actions. According to Kaplan and Norton’s approach to The Balanced Scorecard, there would be initiatives that would take an actual performance measure to a target level.

  4. April 25, 2012 at 10:00 am #

    Bradford, thank – I couldn’t agree more. Once you get a metric that says to “do something”, say a flashing yellow or red light, the next step is to have some agreed upon, standard process to solve the problem or exploit the opportunity. This could be a problem solving process you mention.

    What got me thinking about this was reading The Power of Habit. The same cue – say stress, could cause 3 people to automatically launch into 3 totally different routines in search of relief (reward). One might go for a run, one might take a drink, one might go on a shopping spree. Once habits are established they become, by definition, unthinking and also become somewhat invisible. In a business context, this might look like a yellow light showing up on a dashboard. Mary might call the customer, Bill might escalate to his supervisor, Gregg might wait 30 minutes to see if things sort themselves out. By attaching a standard routine or process to the cue, ideally you’d get all three performing the single best process to solve the issue.


  1. What is your model for business success? | Successful Workplace - July 17, 2012

    […] A smart organization needs to capture upside, cost and risk measurement as part of efficient and wise operations. The model is the place to ‘hang’ information for execution of strategies to maximize opportunity, keep cost low, and manage risk. Business Intelligence (BI) is in the midst of transition for this very reason…it hasn’t been friendly to business models and served up ‘free floating data.’ […]

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