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Big Data Success Formula: Awareness + Understanding => Opportunity

Updated: Apr 10, 2019

Everyone has the desire to make an impact (on various levels) throughout their lives.  The challenge is to find folks who "think" like we do and have the desire and resources to act up on aligned thoughts to effect change (could be on any dimension).  But, most of our time is spent convincing others about "our ideas" and then trying to get them to apply resources (their time and money...and perhaps others) to implement those ideas.  That is why so much time and money is spent on marketing, sales, and consulting analysis (not necessarily implementation).  The challenge for all of these folks is trying to get someone (lead, customer, member, partner, associate, or even a friend) to "see" the problem or opportunity with clarity.   The challenge is that the way the problem or opportunity is framed, can bias the reality (and scope) for what should be done and the best approach to apply in achieving the right results.  

We see this every day as these discussion unfold between provider and consumer (and yes, between physician and patient). The challenge for the consumer is one of framing.  How do they frame the problem and/or opportunity so that it represents what is contextually relevant to the jobs that they are trying to get done ?  How do they know that the right scope is presented and that they are solving the right problem or that the right solution is being applied (even if they know the problem is properly framed) ?

Consumers are fairly adept at matching a products/service which meets their needs once they can connect the dots between a properly framed set of unmet needs (problem or opportunity) and the capabilities and results (perhaps laid out in a story or shown as demo) that are offered by a product or service.   But, the challenge for the consumer is how do they frame their problem / opportunity in an environment where the level of complexity and the pace of change is accelerating.  [we used to live in a world where "change happens", that's still true but it's no longer constant change, now it's accelerating]

We now have the capability to "see" more clearly when identifying problems or opportunities.  The advent of Big Machine processing (democratized parallelism in computing...if you will) and the availability of Big Data (the amount of available data that helps us properly frame the problems / opportunities in their entirety) can be used to create better awareness and understanding. Big Data (not a fan of that term, but it is popular), has the potential to transform organizations and the age-old dynamic between provider and consumer (esp. in Healthcare).  This "potential energy" (if I can use that metaphor) will likely remain in that state until the data can be properly framed by contextual relevance (let's call the metadata for now).  

Example of contextual relevance:

Suppose I come across a new tool.  I have never seen this before and would have no desire to use it (let alone purchase it). Then, I see another customer walk up to that tool and talk about how "he/she" uses that tool on her job.  I don't have the same job as this other customer, but I am trying to get similar things done around my home ...AND this tool suddenly becomes relevant once I understand how it can be applied and used.  Of course, I might see a neighbor using the same tool for a very different purpose and discover yet more uses for the same tool  The tool has not changed, but my awareness and understanding of how to use that tool has been expanded and THAT increased contextual relevance allows me to further leverage the same tool.  

Just imagine how contextual relevance can impact the way we use data to help us get our jobs done.   Now, you can get a glimpse of the power of data and the importance of framing it (using contextual relevance) to realize the full value it can provide.  Again, the availability of data exists, but it's only useful once we can use it properly to gain awareness and understanding.

Now, we come to the next problem that compounds complexity and challenges consumers ability to clearly understand a given problem or opportunity.  The amount of data that exists is already more than we can consume.  So, our old reliance on reports and 2nd generation analytics (multi-dimensional cubes), are fast becoming irrelevant.  We need a new way of conveying understanding with the growing amount of data.  Conventional approaches for conveying awareness and understanding (let alone attempting to explain how a product / solution can address the consumer's unmet needs) is becoming increasingly difficult.  Here's where advances in visualization need to be brought forward because Big Data is a compounding problem and conventional methods of conveying awareness and understanding through reports, dashboard, and analytics are simply not able to conquer the data or the growing number of patterns that may exist in the data. Providers tend to "simplify" the complexity since they themselves are overwhelmed or there are some who are leveraging (and even pioneering) techniques in visualization to help improve their ability to communicate awareness and create understanding.


Example of visualization opportunities:

Imagine (in a few years) when your DNA will be available for your doctor to review along with your EMR (electronic medical record) and statics from the CDC and other sources may be brought together for a diagnosis for your overall health and/or a medical problem (in specific).  The conversation might be awkward at best if the doctor does not have a command of the patterns (that pertain to your immediate problem) and worse if the doctor cannot identify probabilities of causality or perhaps indicators for predicting mortality (you might die and you won't identify root cause until it's too late).  There is simply way too much information for the physician to "mine" through using conventional tools.  A whole new set of tools will need to be brought forward so that your physician (and any other physician for that matter) all see the same pattens and indicators to properly guide diagnosis and treatment.   Even better, is the enormous amount of data that can be brought to bear on the side of prevention, which would bring costs down for healthcare in general.  But again, this would only exacerbate the complexity facing physicians with diagnosis.  So, these are just a few "use cases" where improved techniques in visualization are needed to augment awareness and understanding. 

Putting it together

So, we have Big Data, we have Big Machines, we are building and extending our contextual relevance around all this data and we're seeing advances in visualization to help create awareness and understanding.  The potential for applying this in helping consumers more fully understand their problems / opportunities will greatly sharpen the focus for the providers in identifying solutions that meet the consumer's unmet needs.  The possibilities are all we have to do is spend some time to understand how to capture and measure unmet needs for customers (see earlier posts) and marry them up to the patterns of problems and opportunities to complete the mapping exercise to solutions (products + services).   


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