Data itself is useless. It is the act that follows the interpretation of data is important. This is nothing new and has nothing to do with the digital revolution. Individuals or companies that fail to use all data at their disposal are underachieving.
Over the ages, people have always invented techniques to make data “actionable”. One prime example invented in the 12th century by Italian merchants is double entry book keeping, which is still the basis for all accounting today. The sheer amount of financial transactions threatened to overwhelm merchants. They were loosing the transparency of their business, they lost track were their business was heading. Double entry book keeping changed that and continues to do that today.
Another example of making data “actionable” is the Chief of General Staff System invented during the Napoleonic Wars (1802 to 1815) by Napoleon and Marshall Berthier himself and perfected by the German General von Gneisenau and von Moltke. In a war of maneuver, it is key to march massive armies “separately and strike together” (Helmuth von Moltke, 1800-1891, Chief of General Staff). This was too much for the traditional military leadership organization. All data from reconnaissance on enemy movements needed to be taken in: Enemy numbers, speed, disposition, morale etc. needed to be brought in relation to own troop disposition, supply and fatigue status, capacities of roads and depots, weather etc. Options needed to be evaluated and decisions to be made – in real time and as fast and good as possible. For this, a group of military specialists, staff officers under the leadership of a chief of staff, which in turn is subjected to the commanding general, has been invented. A large part of the success of first Napoleon – and later Moltke in the spectaculary successful wars against Austria 1866 and France 1870 – rest in the refined chief of staff organization. In other words: The superior capability to act on data with superior decisions, fast, shaped the future of armies if not of nations.
Companies who fail to come up with actionable interpretations of data will deliver inferior results. This learning is not new, but the bar has been raised by the digital revolution:
- Data amounts are massive
- Data sources have multiplied
- Data processing capacity is available, cheap and fast
In the short term, there is nothing to prevent a company from continuing in its old ways of handling data. But they will face certain doom over time as soon as competitors are coming in, who are using those massive amounts of data, mesh up all these data sources in a meaningful and reliable way and are able to process and re-process the data again and again to test and falsify hypothesis. They will continue to learn and serve the customer better and better, beating the competition.
Competing against an incumbent company that is ignoring big data is like competing with a half blind and deaf hunter during a prize hunt. It does not matter too much how much skill, wisdom, strength, endurance the hunter has, his lack of senses will make every other capability worthless.
Admittedly, this is a very strong statement. After all, competitiveness is so much more complex than just good corporate intelligence and decision making. In addition, better capabilities in these areas will deliver some value, but there is a continuum between “some value” and “overwhelming competitive advantage”. It takes a lot of time to build up good analytical capabilities. So is delaying an option? After all there are so many beneficial corporate projects to fund.
The technical part of the challenge can be used relatively easily, technologies are there, even on demand via cloud solutions. The cultural part is the real challenge: Making data “actionable” and use these insights as an additional data point in decision making in management processes is incredibly tricky. Most organizations rely on the HIPPO principle of discussion making: The highest paid person in the room decides. Surely, this is a feature of all autocratic organizations, of all hierarchies. The benevolent autocrat may listen and weigh arguments raised by the team against his background experience. Still, this principle has three problems:
- Massive subjective bias
- Slowness, as decision making takes decision makers time to immerse herself in the topic at hand
- Responsibility of results shifts to the decision maker, away from the team
More and more, the focus of a manager shifts towards making decisions under uncertainty and making them fast. Relying on a superhuman, omnipresent manager will not get very far. The key to answer this challenge is to allow for more autonomy of local teams and workers. This is a massive shift of culture. If this transformation journey is not started without delay, time passes on the critical path of digitalization. This is time ultimately lost, without chance of retrieval if faced with competitors which are on the way.
Big data is worthless without a cultural revolution, a new work organization which changes habits, values and – over time – culture. How should that look like? Lets take a look at that in the next blog post.