Recently I wrote a blog post celebrating the change of our name (A New Direction, 2015) and our company’s new direction into data analytics and digital marketing. In that blog I suggested that science is forevermore linked to marketing and communications. The reality of marketing today is that if you are not generating meaningful, measurable results than you are still working in the past and risk being left behind.
Many Chief Marketing Officers are fearful of changing direction to campaigns that are uniquely different. Many CMOs are also in the prime of their careers and have earned the right to set the strategy for the brand. Some CMOs may be asking themselves: Why change now when so much of what I have implemented in the past is working today? Why risk my legacy in favour of a trending topic?” Or do I even have the skill set or time to learn such a dense subject matter?
A recent survey conducted by Deloitte Canada found that 51% of CMOs said they “do not have the in-house skill set to harness data” (The survey of over 300 Canadian CMOs was conducted by Deloitte Canada and the Institute of Communications Agencies [ICA] and were presented in January during the FFWD Advertising and Marketing Week conference in Toronto).
Furthermore the Deloitte study found that 71 per cent “overwhelmingly believe … that harnessing data analytics is one of the most important challenges they face.”
So where do you start?
Here are four simple steps to consider when launching a program.
I believe the first step is to determine the business need for data analytics. You must look for attainable wins that justify the existence of a data strategy. In other words, find a problem that can be monetized into something meaningful to your company’s bottom line. Look for low hanging fruit, such as internal data processing, organizational data harmonization, CRM and more.
The second step is to assess data analytic skills you have in-house and the augmentation or complete outsourcing to an agency that specializes in data analytics. This can be tricky if you are not familiar with the subject matter, and I would urge you to seek an expert to consult on your requirements. If you are not sure of the requirements of assembling the right team, keep following our blog as I will be writing about this subject soon.
The third step is a careful inventory of existing data, systems that your company currently owns, and external data that may be required to launch your program. This can be overwhelming. I often hear people say “we have so much data but no idea what to do with it” or “where do you start?” Which takes us to step four.
The fourth step? Keep it simple. Don’t try and tackle the world in one massive program that may yield zero results. The invention of Apache Hadoop has lowered the barrier to entry for Big Data analytics, as storage and processing power can now be completed in the cloud at minimal costs. Companies of all sizes and all industries can enter the sphere of data analytics. SMBs can now compete in the space and in some ways have the advantage of being more nimble as there is less bureaucracy preventing projects from moving forward.
If you’re still scratching your head and questioning whether Big Data is worth another look, here are some compelling facts:
In a recent article in the Guardian Sue Unerman of Mediacom said, “You can’t just fix it overnight. You, your clients, your partners and your systems all need to adapt.”
Start small and don’t be overwhelmed. But start soon.