"We Are Always Almost There…"

by Varun Gupta

As an entrepreneur following the lean startup philosophy, how do you know when to stop pivoting and pull the plug on your venture? Is this decision easier or harder in a lean startup?

“We are always almost there… “

The temptation is immense to keep tweaking, to go on ‘refining’ the business model, or keep ‘improving’ the product, to believe that you would create the next Google if you just changed that one thought glitch. That’s what an iterative, feedback-loop based, pivoting lean startup could mean.

Or, it could mean, I’ve tried the 6 different options there are to doing this, but the market is non-existent. Does this indicate a defeatist attitude or just an acceptance of reality? Difficult to tell – entrepreneurs who have gone on to make billions pivoted what might now seem to be just often enough and at just the right times.

The decision to making that one more pivot is made tougher by the low barriers to doing so in an info tech setup – the physical and intellectual infrastructure is seemingly in place, there is usually a low monetary cost of execution and relatively little time investment before a new prototype is brought out. Adding to the confusion, from a market development perspective, a company built to learn has to decide how much to learn from early adopters and how much to be stubborn about. Steve Carpenter (Cake Financial) ignored a few customer demands that he believed were misaligned with his idea of what the product must look like. However, if what you are bringing to the table is a breakthrough product, can you always trust the signals given by early adopters? From an operational perspective, Kent Beck, the creator of Extreme Programming, says that the first step in a lean transformation is learning to tell the difference between value-added activities and waste. While he was probably referring to the practice of failing fast and learning enough for the next pivot, it might be extended to include not pivoting at all if the process for assessing what comprises waste is thorough.

To “escape” the iterative process, and to avoid waste, entrepreneurs must be careful to not get accustomed to the rhythm of churning out a prototype, satisfying a VC, seeing the product fail, outlining changes before the next VC presentation, and spitting out a new prototype. Ask yourself often enough about where you want to be. Listen to yourself. Secondly, entrepreneurs must be honest about the investors they pick – pick them more for what they have to say to you and not always for what they have to give to you. An info tech startup may not always have the luxury of being able to pick its customers, but it can sure pick its investors who can be trusted for feedback. Picking investors is as much about your evaluation of them as it is about their evaluation of your typically “phenomenal” idea. Listen to your investor-advisor. Finally, don’t play the numbers game. You are not likely to get the desired result only because you’ve explored all options and made enough pivots. If you were operating in a vacuum, that may still not be possible, and when the product is based on customer habits and two-way interactions, there is no exhaustive approach to tech venture success. Listen to your customer.

I’ll end with a somewhat off-topic comment, but worth mentioning, since it’s been a nagging thought: Eric Ries visited class and made a statement equivalent to, or maybe more outrageous than, Goldman Sachs chief’s comment about how bankers “do God’s work”. Eric mentioned that his effort and those of some others in the online social media industry are helping resolve an evolving social issue – that of social isolation or increasing introverted behavior. I’ve read at least a couple research papers, and am sure there’s more of that out there, blaming the advent of social networking in making people socially deficient, self-conscious and isolated as compared to the days when people had real interactions. I wonder if entrepreneurs sometimes create such reality distortion fields (used in a loose sense) to give them a reason to keep working at developing the next “social” phenomena. Do such RDFs make the decision to quit even harder?


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