I moved to Australia from Belgium two months ago for a short-term assignment. I am very concerned by the exchange rate. My dollars have lost over 15% of their value in euros and I share my frustration around me. People tell me, "Just wait, it cannot stay so low, the rate will go up again". So I keep waiting.
Actually, this intuition is against all economic principles and historic observation. If there was information on the market indicating the value of the dollar is underestimated and will go up again, it would be immediately incorporated in its price. Making the intuitive assumption that the dollar will come back to its historical value is like buying a lottery ticket. You are only buying a dream. It has the exact same likelihood to go up or to go down again.
Yet, I am taking the decision to wait. I don’t need the money now, and I buy the dream that the value of the dollar will rise again, with an eye on the next iPhone I could buy with it.
Many organizations have to take the exact same decision as me.
If you were an executive in a company with Australian dollars in the bank, shareholders in Europe and no local investments in sight, would you wait? Would you consider it a rational decision? Can you afford the same subjectivity as me? Can you buy the dream the value will rise again?
Doing business is taking decisions and companies cannot make subjective decisions. All business decisions must be treated with a maximum level of objectivity incorporating all available information. Whether these decisions are strategic, tactical or operational is irrelevant to this principle. So, organizations cannot buy the dream the dollars will rise again.
And it is a challenge for many organizations to get rid of that subjective bias. They must engineer their processes in order to take optimal decisions, requiring the right information at the right time. This information consists of analytical insights, patterns, sentiments and anomalies hidden somewhere in data. It will require to read, store, crunch and process tons of records, texts, trades, news and databases at extreme speed to meet the decision timeframe.
This process must start by defining the decisions that the company want to objectivize. The price of an airline ticket, the purchase of additional ships for oil prospection or the insurance premium of a policy holder.
These decisions define the insights needed for improvements. It may be simply surfacing the most recent update about a customer. It may require some probabilistic computations of oil prices or sentiment analysis based on previous phone conversations.
And only those expected insights will ensure the organization put up the right data requirements. What data is needed to provide these insights? Comment fields, sonar echoes, phone calls, pictures? Is the data to be stored or only processed? Where and how does it have to be stored? Etc.
Organizations must aim at decreasing the subjectivity of decisions and this process must drive the requirements for technologies. As such, decisions will define the analytical strategy, and analytics will define the data strategy.