In my previous post I wrote about organization structures. One interesting thing about them is that Startups want to become big corporations, but more than 90% of them fail. Big corporations want to have “Entrepreneurial structures” but they normally fails in its implementation. Let’s try to understand this confusing behaviour pattern.
One of the organizations structures that we’ve mentioned in the previous post was the “Entrepreneurial Organization” that has a flat and simple structure were everything is relatively unstructured and informal making this type of organization fast, flexible and lean.
Probably is the model that most companies want to copy but in most of the cases those companies looks more like a character from Cocoon than a real young and full of energy teenager.
Entrepreneurial Organizations are not more effective itself. They are flexibility, fast and lean basically because they are tightly controlled by the owner/entrepreneur who concentrates all the decision making power and vision. One of the most difficult things that the Entrepreneur (the owner of the vision) can transfer is the vision. The vision is the conceptual framework that allows making decisions that make sense for a particular company, in a faster way without interacting with others.
That’s why when this kind of organizations grow, their structure can be inadequate as decision-makers can become so overwhelmed that they start making bad decisions. This is when they need to start sharing power and decision-making, but since the vision can not be transfer in 100%, then moving to another structure is key to generate an “artificial decision making framework” to replace the vision.
The artificial framework is what explains (or generates) the specific behavioural pattern a company has. Having sensors to measure the decision making flow in a company is the best way to avoid unintended behaviours that can become part of the company culture, ergo, part of the “artificial decision making framework”.
KPIs, or key performance indicators, are effective in measuring performance of isolated functional áreas or departments of the company (Marketing, Finance, Operations, Logistics, etc) but extremely complex to successfully integrate metrics that allow understanding the company as a whole with a common objetive (making money). For example, Brand Awareness can be presented as a KPI that shows the company is achieving its business results. However you can have a recalled brand that doesn’t make money. So Brand Awareness is not a business performance metric itself. Nor does Facebook Fans, Twitter Followers, Pageviews, etc.
The way we normally use KPIs to understand how a particular are or action is bringing the company closer to its business result is by using metric connectors. The Metric connectors allow us to understand how a KPI (that measures performance of isolated actions) is generating an impact in the company business results. Following the example above, to see if there is a link between Brand Awareness and future sales you have to conduct a survey with a panel to see if there is any relationship (Co-variance analysis) between Brand Awareness and Purchase Intention.
As you can imagine, the complexity increases as the company gets bigger, making almost impossible to keep those Metrics Connectors updated.
So companies must focused on developing a data driven culture from the very beginning, even when they can take advantage of an Entrepreneurial Structure. The company must develop a Meta Analytics structure, a layer of information that allows companies to comprehend the flow of interactions that the parts of the company (system) are generating and how those interactions are bringing the company closer to its business results.