We are all hearing about Big Data – The question is what is about and how it effects our daily business.
How Big Data is helping Marketing research to lead from front
So what exactly is Big Data? it is nothing but a large number of complex data coming from multiple sources. From business perspective I don’t agree with the general definition of Big Data.
In my opinion, Big data that is useful for the businesses is the huge amount of semi-processed information coming at a fast pace from multiple internal and external sources.
Is it something we didn’t prepare ourselves for? For experienced staff that has spent years in marketing research and/or information management and/or knowledge management I think they are prepared for it. But the new joiners and the close to retirement staff are the ones where we might experience problems in terms of handling this large amount of data.
As information managers, I suggest we ask the following questions from ourselves before we start to follow the flow.
- How can we capitalize this information?
- How can we accelerate our career progression through this data revolution?
Capitalizing the information – The Forte of Marketing researchers
- Apply the 80/20 rule: 20% of the information streams can be translated into actionable business decisions. Focus on that. I usually take a top to bottom approach i.e. which business decision is most important for the organization, what type of information is required to facilitate that, where are the sources of information (have a look at this data to decision value chain)
- Present the solution not the finding: An eye-catching dashboard is worth a million words, but a jaw dropping solution is worth a promotion. It is about time; we (the data analysts) come out of our shells and start proposing business relevant solutions. Solutions about people, processes or the product.
- Simplicity: Simplicity is the key. No matter how complicated the data is and how difficult the solution selling is. If your presentation is not simple enough then you haven’t done your job well. Cut through the chase, get to the point. And get to it as fast as you can.
Emerging Fancy Designations: Now, we are hearing about a lot of emerging designations in the field of information and decision making (you may also want to read this article about Data Scientist by Harvard business review). But essentially what will be the job description of all of these designations? I think Recruiters will expect you to Turn Numbers into Stories: Find out trends, discover insights and propose solutions. And you can do that, if you have the following skill-set
- Software programming: Basic understanding of SPSS, SAS and similar software and ability to run complex analysis. Many believe that coding will become the part of the job description but in my opinion that probably will not happen.
- Intense Curiosity: The real insights and solutions are discovered by combining observation with trends. If you can see something in the data what others can’t then you are the person for the job. But if you can’t bring anything new to the table, then you must change your career.
- Business Orientation: Understanding of processes, product development (which can be a bit of engineering too), understanding of marketing and understanding of finance will be essential for a good researcher to propose effective solutions. So you must be an all-rounder.
- Communication: Translate the number into a mouthwatering insight visually, verbally and in writing. (I admire the way Simon from Team Y&R narrates his stories, here is an example. May be we can learn a thing or two from his articles)
- The C-Suite: Gone are the days, when number crunchers were the back office under paid staff members. Today; if you can derive meaning from the data you can actually aim to join the C-Suite of the organization. All you need to do is to negotiate, negotiate and negotiate. I will quote my Ex-boss, “never ever under sell yourself”. The skill-set is very rare and is in demand. This will be the only skill-set where the numbers of jobs are higher than number of people who can do this job. So don’t undersell yourself.
Big Data, Bigger Myths by Accenture
Big Data – the next frontier of innovation by Mckinsey