It has recently been said that data is now more important or more valuable than oil. This makes for catchy headlines that attract readers, but the analogy doesn’t always seem to hold.
There are some parallels that make the analogy seem fair, like how data has been used to unlock massive value for companies. Another seemingly fitting likeness is how crude oil must be refined through a relatively complex process into usable fuel. Raw data also often must be painstakingly transformed into a usable form for advanced analytics to deliver real value.
There are various points where the analogy breaks down, among which the transport, durability, and reusability of data compared to oil. Another critical point of breakdown of the analogy however seems to be the knowledge of data owners of how to unlock the value of the data that is already gathered.
Many companies go to great lengths to collect and store data. It is as if somehow, we always knew that there is inherent value to data. Companies will gather terabytes of historical data and pay large sums of money to store the data, without really getting much in return.
Then along came awareness about a set of tools collectively called data science. Much of the technologies that currently form part of the data science stable is not new. Modern processing power, increased capacity for data ingestion, and awareness of these technologies have however led to a surge in data science implementation and use cases. This leaves companies that have painstakingly gathered data and do not see any return with the question of how to unlock the value buried in their data. Without acting, these companies may see themselves being left behind as other industry players gain a competitive edge while putting their data to work.
The first step towards unlocking this value is to start with understanding what is possible. Data science is often touted as a silver bullet that will solve all your problems. It is important to understand, or be guided, towards what you can achieve and importantly what you cannot achieve. Investigating use cases in your industry may help to get you started.
Another important step in unlocking value from data is collaboration. It is important for advanced analytics practitioners, who understand the available technologies, to spend time with business practitioners that understand the business requirements and what is contained in the data. Without such collaboration you will be left with data scientists that continually grind their axes on toy datasets and businesses seeing no return on their data investment.
A good approach to this problem is to think big, but to start small. As a company it may be prudent for you to implement large-scale data analytics solutions, an endeavour that may seem daunting. It will then help to start with smaller, agile initiatives that will deliver value in the short term. Longer term analytics projects can then be started on the back of these previous successes.
Acting on these principles, your company may soon start seeing value from the data investment you have been making for so long.
At Onpro Consulting, we combine effective business consulting with state-of-the-art data science solutions