Tuesday, September 18, 2012

In Search of Predictability

If you listen to the emerging trends in Corporate America, you will hear conversations about the importance of reading enormous amounts of data. The current belief is that there is so much data that more people in the organization will need to develop skills to analyze it. Currently, those skills have belonged to people in the IT department. However, there are individuals in other business units that may be able to combine their knowledge of customers with the ability to assess data.

On the surface, this seems like a logical step. In the age of knowledge workers, businesses should better utilize the intellectual capital of human capital. This would seem to help leadership better understand and predict customer behavior. As a result, strategy becomes much more clear and predictable.

From another perspective, if companies stop at developing skills to analyze data, it will be the catalyst for
their undoing. Data is backward looking. It can only tell you what has happened. Human beings, on the other hand, are forward looking. We can alter events in the future. We have no access to the past. The past is gone. In fact, in today’s fast paced environment, by the time we receive data, the trend may have already changed.

If we immerse a larger percentage of the organization in data from the past, the new strategy could be obsolete before it is typed into the computer. Therefore, it may be better to use data to explore micro trends that seem to have no relevance to the current business model.

At the same time, there are possibilities that you can never find in data. Those possibilities are often ignored because they appear irrelevant. The reason for the irrelevance is because there may not be one single consumer for the product or service and the margins appear to be low.

For example, in the 1960s, the Japanese automakers introduced compact cars in the US. Before Japan arrived, there were no consumers for small cars. It was a non-existing market and there was no data to prove there was a market. 

Japan entered and found buyers. For US automakers, purchasers of small cars were irrelevant because margins were too low. Therefore, the US continued making big cars.

Over time, Japan went from making small inexpensive automobiles to luxury cars like the Lexus and Infinity. There was no data to predict this phenomenon would happen. Yet, those small insignificant Japanese carmakers are now stealing market share in high margin cars.

I am explicitly warning that an over dependence on data will cause many organizations to miss non-consumers that are hidden in plain site. Look in places like Mongolia where many people do not have access to electricity. Those people are buying inexpensive solar technology. Why? It is better than having no electricity. At one time, they were non-consumers. 

Businesses have to start thinking about who are the non-customers and why are they not buying. Those trends may never show up in data.

Ensuring more people in the enterprise can read and aggregate massive amounts of data will be important. At the same time, it will be essential to look for what data cannot tell you. While many people will say, ‘the reason no one is selling to them is because there is no market’. That is just an easy way out. And it can be the death of your business.   

What do you think? I’m open to ideas. Or if you want to write me about a specific topic, let me know the subject.  

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