How can you stop short term choices from crippling long-term value?


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As more bad news about Wells Fargo’s practices emerge,  the stain transcends CEO Stumpf’s  reputation. Warren Buffett opted to wait and comment knowing that he himself needs time to sort through his own internal review process.

It’s not just Stumpf who needs to believe that the “cancer “found in the retail bank was its source. The Gr8 prorgram setting very high bars for growth with 8 interconnected accounts per customer delivered results but discovery of the ill effects  proceeded much slower.  It took years and then the decision to remove the malignancy—firing of low level employees and managers—what made management believe this toxic behavior didn’t spread?

Well that’s naïve, if not ridiculous, isn’t it? Elizabeth Warren made clear that an organization must remain accountable to its customers more than its shareholders, no matter how large or successful it becomes. Somewhere along the line Wells Fargo, Samsung, Chipotle, VW, and GM all made similar high profile mistakes.

Speed to market may appear an appropriate competitive response but not if short-cutting quality results in shortchanging business value.

Bottom line the antenna in a business can’t be only tuned in for reward especially since it often means the business misses the risk signals. The obsession for rapid growth isn’t just blinding good judgment shows in ignorance of the environment and its complexity.

Interconnected digital networks absolutely create a speed advantage. But speed needs to be managed, and adjustments made to acknowledge the additional risk it creates. Ask the NASCAR drivers what precautions they take that are absent in other environments, or the Samsung engineers who knew they hadn’t done enough testing to properly advise the risk management team with information that prepared them for the inevitable fire.

Pull not push

The Internet made it easier than ever for consumers to find anything, anywhere, and at anytime. Businesses and sales people need to adjust and adapt to accommodate these more informed buyers. At the same time management goals or quotas must recognize changes in the environment, but looking more broadly at the inevitable interactions and the change in likelihood that they will occur.

It may be a cliché, but it isn’t true that what got you here will get you farther. What worked in the past works differently today and will work in another way in the future. The trick is to find the part that is essential and remains critical. Water does seep to the lowest level, but technology advances have created stronger more resilient and resistant containment mechanisms that alter the impact.  Don’t wait to understand them until it’s too late.

Start by answering these questions to the satisfaction of your leadership team and board.

  • How does your management team leveraging or limiting the new levers of change?
  • How does social media, sensor networks, big data and cloud computing alter the behavior of your customers?
  • What risks to your bottom line do they introduce?
  • What steps have you taken to mitigate and or adjust your targets to assimilate them?
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How Framestretching adds clarity


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This morning on Twitter @Bedtimemath posted the image above with the caption that read: “A natural distribution spotted in the wild! The wear on a weight machine reveals where people place its pin.

Though we experience life using multiple senses-sound, taste, touch,scent and sight, how much do we actually use to understand our place and actions?  Consider this two dimensional picture, the visual more than likely drives the meaning we make. Did the words add any more meaning to what you understood in looking at the picture?

Last Friday, the strategy discussion I lead monthly talked about visual thinking and I realized how readily my business training reduces most if not all of the perceptions available through my five senses down to only one or two.

At work, we use words or numbers and rarely put both together as well as this tweet and accompanying image.  This visual asks you to interpret the worn out paint or coating and recognize a normal distribution , which is a statistical explanation that adds another dimension to our understanding.

Could you plot a graph with the information you obnormal-sampleserve?  How about wear vs. weight?  That’s only two dimensions, with weight values on the x or horizontal access, and wear shown on the Y or vertical access.  It might look like the two dimensional graph on the right.

Does this representation tell you anything more than  the original image? I assigned numeric values to the different amount of chipped coating. Do you connect the current location of the weight on the machine as  170 across and  estimate as I did 20 up?

Both image and graph show, but don’t tell as much as we assume.

Where’s the context? Do you know the amount of time it took for the paint to chip or relative distance between observations, or usage of the machine itself?  We know nothing about the users of the machine, or its location and yet we do don’t we? The rust itself takes time to form and we can infer that more users choose at least 50 pounds, and the most users 90 pounds.

More than meets the eye

Next time you view a two dimensional graph–ask yourself what’s missing?  Try to voice and articulate the context that you’ve assumed. Yes even if you do it alone, as hearing your thoughts activates different processing.  When you do it in the company of others you will be surprised at the differences in your understanding.

I happened to see that DataScope analytics, a Chicago Based Data science firm had posted a request under data science on Reddit.  They asked “What data skills do you wish non-data people you worked with (e.g. managers, PMs, marketing, HR, etc.) have?  The responses on Reddit were quite fascinating.

Personally, I couldn’t help but notice how the replies typified the  constant challenge and struggle that any information or data presents to everyone.  What does the data mean, what is it’s significance?

The same themes arose in the conversation among business people exploring the challenges of visualizing data, in which we quicly recognized that few people see the appearance of data and instinctively look to explore it, versus others whose interest in data are for the sole purposes of confirming what they know.

The questions and process with which anyone approaches data obviously informs how it gets used and thus represented too.  Too often we use only one or two dimensions as suggested by the graph of the interpretation of the photograph.  I created the variable wear based on my interpretation of frequency approximated by the degree of chipped paint.

In contrast, the two dimensions suggest more than they reveal about how the world works.  Economists, for example, plot  supply and demand curves that look like a large X.  Supply being the first line that descends vertically, and demand the second line that Ascends.  The vertical access is Price and the horizontal access quantity.

What else is  assumed in this representation?  Geography? Time?  what about probability and or frequency?  Accuracy or specific observations as in the photograph are not the point of the representation.  It’s merely to create a general understanding of the relationship between price and quantity from two different perspectives.

The economists are exploring  and not predicting behavior, they are merely seeking ot make sense of the world not necessarily profit from it.

Further explorations that southt to clarify the assumptions led to the evolution of the  behavioral economists and  their additional perspective enahances general  understanding  of people’s beyond the one dimensional buyer or seller role and expanded the representation.  The inclusion of additional dimensions of probability also introduce additional complexity in exchange for greater understanding.

My own training as an analyst has led me to begin with exploration, and interrogate rather than merely to extend or convert  the representations. There’s always ore than meets the eye when it comes to understanding what we see.