Formula for Govtech Success
Successful businesses have systems that maximize (or minimize) a very small number of variables. Amazon is one of the best modern day examples of a company with a simple strategy, executed beautifully.
Amazon’s strategy isn’t unique. Every e-commerce company has (or should have) the same strategy. They all care about the same key variables; customers, sellers, inventory, and experience. This is typical in mature industries, companies converge on a similar strategy for growth. An early company finds a growth formula that works and other companies follow.
Once the formula for a particular industry is established, competitive advantages are created in the execution layer and accentuated through scale. The best founders (Bezos) recognize the formula early and get a jumpstart on execution. The worst founders toil away on complex strategies and waste precious execution time, typically resulting in failure.
I’ve spent the last few months looking for patterns of business success in govtech. I keep asking myself, is there a formula for success? I think so. The formula for govtech success looks like this:
(Differentiated Data x Customer Concentration) ^ User Experience
Just remember; (1) Industries normalize to shared strategies, and (2) Competitive advantages are created in the execution layer and are accentuated through scale. The formula is about the forest, not the trees.
Differentiated Data
Data that only you or a very small number of people have access to at any given time. Differentiated doesn’t necessarily mean proprietary, it simply means limited access. Providing “insights” on undifferentiated data isn’t enough. Access to differentiated data enables an informational advantage of scale. Differentiated data may become open and available over time, but at that point, the best companies have already built their competitive advantage.
Customer Concentration
The clustering of customers by either geography or domain expertise. Government agencies will always be risk averse. The most effective way to overcome this risk aversion is through social proof. In govtech, social proof is generated by references from nearby agencies or individuals with the same expertise and workflow. Customer concentration enables social proof advantages of scale. In turn, it shrinks the sales cycle, increases renewal rates, and more often than not fuels acquisition of more differentiated data.
User Experience
The user experience in govtech is more than just the product. It’s the sales process, customer onboard, and the product experience. The best user experience enables cost advantages of scale.
Applying the Formula
The formula is intended to be more strategic and less specific in it’s application. For example, you could give each variable a 0–5 score and find that the very best company is 10,000,000x better than the very worst, which may be true, however that’s not the intent. Amazon surely doesn’t score “Maximizing Selection” on a fixed numeric scale.
Strategy is about maximizing (or minimizing) a limited number of key variables in a context specific to your business. Govtech companies have different flavors and work in different subcategories. For example, differentiated data in company focused on transportation looks different than a company focused on citizen engagement. In both examples, differentiated data is still required to build a good business. The same goes for customer concentration. One company might choose to focus on a specific geography while another may focus on a domain niche. Both of those companies are better off then a company that doesn’t try and cluster their customer base. The point is, successful govtech companies maximize these variables.
I anticipate the most contentious aspect of the formula is the order. Specifically, the fact that user experience can only amplify the base value created through differentiated data and customer concentration. The reason is simple; a great user experience built on undifferentiated data has a short shelf life. The competitive advantages are limited. Having access to differentiated data, combined with a customer moat, buys time to get the user experience right. The opposite just isn’t true. If all other things are equal, then yes, a better user experience will have a multiplying effect.
Only time will tell if this formula is accurate. I suppose I would rather be wrong, than not have an opinion at all. :)
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