Many of you have undoubtedly heard the phrase, “Data is the new oil.” It was coined in 2006 by an English Mathematician, Clive Humby. The reference implies several things: that data will become an increasingly valuable commodity, it will be a driver of the economy, and from a natural state, while unrefined, it is of limited value, but once processed, its value increases substantially.
In parallel to the oil analogy with data, the term mining has also become increasingly prolific in the last few years (yes, I sense a gold or diamond analogy in this case). I’ll be the 1st to admit that I see a dual purpose with the term ‘mining.’ In its original meaning, it is digging or extracting a material (metals or otherwise). However, the secondary meaning is what I’d like to explore a bit deeper (yes, pun intended). Once extracted, it ensures value is added to the material to benefit both the miner and the eventual customer.
Aside from data mining, you can now read and study process mining, task mining, and bitcoin mining, to name a few. Are some of these semantics? Absolutely. At its core, and trying to keep ideas and concepts simple, it is getting value out of your data. That data can originate in an ERP, MRP, CRM or any other information system. It can be customer-focused, employee-focused, or business-focused. In my opinion, the overarching theme of mining in a business sense is looking at data to gain insights into past trends and identify means to make processes better *and* hypothesizing future outcomes to determine new markets, products, and a means for growth.
In many ways, there is a strong correlation between mining and CI tools. I associate the mining part of any improvement with the “DMA” portion of the DMAIC process. You need to ‘define’ the data to assist in the improvement. ‘Measure’ is the collection and storage of information in an adequate format. And analyze? It makes up a significant portion of the process. Preparing, sorting, manipulating, evaluating, and presenting the data.
Is mining an extremely beneficial tool? Without a doubt! I think I’ve been a miner longer than the term existed (in this newer meaning, not the original). The need for businesses to understand, use, and efficiently interpret data will help them grow and improve their processes. Relying on qualitative and subjective feelings and opinions, while sometimes a necessary complement to data, isn’t often recommended as the sole approach.
Is data this millennium’s oil? I think that is a disservice to all the analytics that have been done over the preceding decades, and everything that has been accomplished. No, I believe data remains a very valuable source of information, but can it replace people and technology? I’m just not digging that.
Darren