Mining Today’s Gold
The IT industry has come a long way in 50 years or so. From a few machines the size of houses doing very simple repetitive tasks to digital sensors everywhere. This comes home to me when I have to drive to a meeting in a location that I have not been to before. I set up my smartphone to act as a GPS navigation system. I’m not 100% sure I know how it works but I assume it uses a combination of satellites, mobile phone tower triangulation and tracking known WIFI connections to work out exactly where I am and provide real time instructions. I then back out my garage. As I do the digital sensors on my car locate “hard objects” behind me and begin to beep as I get to close. As I drive sensors determine which engine in my hybrid to use, electric or petrol, and present to me real time data on how much petrol I am using or whether my battery is recharging. The computing power and the data that is used and created is phenomenal and all this to meet a friend and have a cup of coffee.
If you put this into a more serious context such as business and scale it up a few million times today’s trend of big data becomes very real. Industry commentators believe that big data offers new areas of competitive advantage to those who know how to mine it.
Mining the data is an appropriate term as you are doing the modern business equivalent to looking for the small flecks of precious metal amongst mountains of valueless “data slag”. So, you want to be a successful data miner but don’t know where to start? Using the mining analogy try starting here:
1. Make sure you know what precious metal you are looking for. Gold is not the only valuable metal out there so you need to be clear which precious metal you are looking for. In data mining this means you need to know what your business model is, who your customers are and the primary way that your business adds value for your customers (ie do you lead through product innovation or great customer service or the best price in the marketplace).
2. Travel to the goldfields (or tungsten mines!) as that is where you are most likely to find the gold. In data mining this means if you know that your business model is primarily about great customer service, for example, then make sure that most of the data you are collecting is based on understanding your customer and their customer experience as this is where the gold is likely to be for your business. Conversely, if your model is focused on efficiency of operations then ensure that most of the data you collect is put in this context. It will be likely that the data you are collecting is incomplete. When this happens set about defining what data you believe you need and begin to gather it.
3. Stake your claim and begin work. Both data mining and gold mining require hard work to be successful however you should also work smart by focusing on those areas that are likely to yield the best value. This means start by focusing on your largest or most profitable product line, your biggest or best customer group or your biggest cost items as these are much more likely to repay the investment than other areas.
4. Finally, keep your eyes wide open! While most miners who made money made it through hard work we all love the stories of the miner who found the huge gold nugget in the most unexpected place (they make great case studies too!). The thing is it does happen and it will happen in data mining but it is more likely to happen if you are open to the unexpected.
Throughout human history men and women have sought riches by mining for precious metals and stones. Our time in history may well be characterised by the beginning of a new form of mining, data mining; where we sift through the vast quantities of data which are being produced as we look for new insights that can add the sort of value that may become the gold of our time. Today as it has been throughout history those most likely to succeed are those who know what they are looking for, they identify the right areas to mine, work hard and smart and are always open to, and seize, unexpected opportunity.