A few months ago I expressed frustration with the increasingly loose and nonsensical use of the words ‘disruption’ and ‘innovation’ in the business context. This month I take exception to another recent, and incredibly annoying, trend …
Everybody is rushing to mine data.
Data mining is the new gold rush.
Data is inarguably a valuable resource and tool, and can create, or contribute to, innovation, efficiencies, and productivity,
Data has also become the latest annoying buzzword. Everybody wants ‘data’, but few seem to know what they are talking about.
Remember, only fools rush in.
For data collection and analysis to add value, and it should always add value, you need to think and plan a little …
Do I have a problem to solve?
The first question to ask is why do you need data?
I recall my mother asking me the quintessential question that all mothers ask their child at least on one occasion: ‘If all your friends jumped off a bridge, would you?’
Collecting and analysing data is becoming just like that: ‘Everyone is doing it, why aren’t we doing it?’
Well, first you should identify a need, a problem you must resolve, a process you would like to improve – an issue that creates a good business case for, and will necessitate and justify the investment in, the collection and analysis of data.
Do I need data?
But, data won’t solve every problem. It’s not a miracle, fix all cure.
You may have a business problem to solve, or a process to improve, but that doesn’t automatically mean collecting and analysing data is the only answer, or an answer at all.
Technology, including data, is like any other tool. You use it when it’s appropriate. You wouldn’t use a hammer to fix a broken bone, and you shouldn’t use technology if it’s not the best or most appropriate tool to solve a business issue either.
There may be other, quicker, cheaper, more conventional methods that will assist in resolving your issue.
What data do I need?
You have come to the conclusion that you have a problem to solve, and collecting and analysing data is not just likely to offer a beneficial solution, but it’s the preferred option.
The next question to ask is what data do you need? You need to understand exactly the type of data you will need to collect in order to solve the problem on hand.
Collecting everything and anything will be expensive, and an utter waste of time. You need to understand the problem you are trying to solve, and the nature of the data that will help you resolve it.
One outstanding example of utilising data to create a genuinely useful and innovative tool is ‘Rare‘, a groundbreaking contextual recruitment system. The tool is designed to remove unconscious bias from the recruitment process, and to create a better, contextualised, picture of candidates, enabling employers to make better hiring decisions.
For example, during the graduate recruitment process Rare removes the focus from the prestige of the educational institutions a candidate attended, and instead zooms in on their experience, skills, abilities, and performance contextualised vis-à-vis their peers, and even considers useful additional factors such as their socio-economic background.
This new method of recruitment is anticipated to have a high impact on workplace culture and performance by identifying individuals with high levels of resilience and motivation, and with diverse experiences and insights – candidates who may have been overlooked in the past under traditional recruitment methods.
Should I use an expert?
I wouldn’t ask my lawyer to perform open-heart surgery, and I wouldn’t ask my butcher to give legal advice.
Data collection and analysis is a specialised field, requiring specific skills and understanding.
Data collection must be aligned with the issue to be addressed, its analysis must be meaningful, and its outcome must be presented in a manner that offers a practical, implementable solution.
It goes without saying that you should make sure that you use people appropriately qualified for collecting and analysing the requisite data. You may have the resources in-house but, if you don’t, make sure you get the right people for the job.
Collecting the wrong data, performing the wrong analysis, or arriving at flawed conclusions won’t just be expensive, but could also result in detrimental business decisions.
Cyber security should always be a base-consideration when it comes to your systems.
However, if you are going to collate swathes of specific data, which may be confidential or commercially sensitive, do give storage, access, and security more than a fleeting thought.
Recent trends indicate cyber security will be an increasing concern, as illustrated by the recent data breach at Mossack Fonseca, which led to the publication of the controversial Panama Papers, the hacking of various Australian government computer networks, from the Bureau of Meteorology to the Reserve Bank of Australia, and the theft of the login details of millions of users of leading professional social network, LinkedIn.
Cyber security should not be a tick-box exercise, or a panicked afterthought, but an essential part of a thorough planning process.
Data is great
Don’t misunderstand me, data can help improve efficiency and productivity, support solutions to business problems, and aid innovation.
It can, but it won’t unless it’s the right tool for the job in the first place, uses the right data for the problem on hand, coupled with an analysis that offers practical, implementable solutions.
And that will take some thinking and planning …
Wise men say
Only fools rush in
But I can’t help falling in love with you …