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Is doing something hard inherently more valuable than doing something easy… even if the hard thing is less useful?
A client has an in-house data analytics team. They do really hard things using tools like support vector machines and natural language processing.
And, we heard some backhanded comments about how our approach to solving business problems is a little too continuous improvement focused and not quite cool enough to really be data science. I definitely take that personally: hence this post.
Here’s my observation (full of bias, I’m sure): the in-house team is aligned to a support function; therefore, they take on data science projects that sound complicated and are aligned to the needs of their functional executive. In contrast, we define our project customers as those parts of the business that generate the revenue stream. We do this so we can better understand value. Drawing from Lean thinking within the continuous improvement space, value is defined by the Customer.
No one else.
While we are on the subject, let us review how businesses add value. A business may do lots of activity. But, a business activity adds value if and only if:
- the Customer is willing and able to pay for the activity
- the activity changes the fit or function of the product or service
- the activity is performed correctly the first time
What does this mean? It means we work on that which is important to the Customer. It means we do not subordinate our efforts in favor of displaying our analytic prowess or employing an exciting tool. Tools are simply what we use to get results. They are not the reason for our existence.
Hence our focus on solving business problems tied directly to the revenue stream and our desire to use the right tool for the job.