5 Tips to build a Career in Analytics
How to build a Career in Analytics – this is a question that I have been asked umpteenth number of times by a lot of people! My answer to most of them has been that Analytics is all around you-you just need to seize the opportunity to apply Analytics in the world of business. Now, this may seem like a motherhood statement, made with the intention of not providing any concrete guidance on how it can be achieved. But, truth be told, the opportunity to make a switch to Analytics as a career, beckons now, more than ever.
Almost every major consulting and research firm on the planet have understood the far reaching implications of Analytics and have started creating teams to prepare themselves for the opening of corporate floodgates to embed Analytics in their day to day business decision making processes as well as to shape their strategic thinking. There is a huge shortage of people skilled in Analytics who can help corporate houses make the most of data that is being stored and generated at a frenetic pace.
Here are my 5 tips for entering an Analytics Career:
1. Learn the tools of the trade – SAS, SPSS, R, and SQL. Start with any tool that you can get access to. Sometimes you will be surprised to find that a Tool that you thought did not exist in your organization actually does. In one of my previous jobs, when I was busy negotiating with SAS for licenses for my team, a colleague of mine, who was an Actuary told me that he had seen a SASsession in one his team member’s PC, sometime back. I followed up with that team member and we found that we had a SAS server already in place waiting to be used!
Learning is not about knowing everything, but learning substantial portions thoroughly and gaining sound knowledge about what you learn. I would much prefer a candidate who knows a lot about how to run a regression in SPSS, than a person who has half-baked knowledge (knows a little bit about CHAID, done a little bit of regression,knows a little bit of SAS and a little bit of SPSS) If you can muster one tool and a few modules/techniques of the tool, then you stand a better chance of getting a job and also of being able to get a job done.
Pick up a tool that is available easily to you and start learning it – SAS, SPSS, R (now available as open source).
I do not recommend using pirated software though they are now openly available in the market.
2. Learn the tricks – If you have learnt the tools, your job is only half done. You need to learn the tricks of the trade. Now there are two options before you- a) Learn from another experienced person/s who maybe there in your organization b) Learn from professional curriculums.
The self-help tutorials will not provide you the secret sauce of Analytics which is very essential for being able to deploy Analytics to solve real life problems. The outputs from running procs in SAS or models in SPSS throw up a large number of statistics. Knowing which statistic to look at and which ones to ignore is one of the most important secrets which only seasoned Analytics professionals will be able to share.
3. Look for an opportunity in your sphere of work to apply Analytics in your present organization. Quite often, people find it difficult to identify where to start. The simple rule of thumb here is to identify sources of data and see if data is being collected in some data repository. If data is being collected in a certain business process or function, the chances are that it is waiting to be used.
Always remember that it is helpful to start with the low hanging fruits. Do not try and build a predictive model at the first go. Your organization will not be ready for such a sudden large step change; more importantly, you will have to earn the trust of the organization before they begin to trust the predictive power of Analytics and of your ability to harness it.
Start by generating simple insights from the data which is not presently captured in the business reports. Create simple metrices which will add tremendous value to the businesses and will get the important people in your organization interested in what you are doing. I was once speaking to a client of mine (who were in direct selling) who had the best BI system in place, but they did not have well defined metrices which could help them leverage the BI system. They did not even know simple facts like:
- Which regions had the maximum demand for their products and needed the presence of a bigger sales force team?
- How are customers responding to promotions?
- Which types of promotions are more successful?
- How many customers and which customers had dual/triple ownership of their products?
- When was the last time that a customer had bought any of their products? (one year back, 2 years back, 3 years back, 4 years back, 5 + years back)
- Customers typically upgraded their product after 3 years- which customers fell into that category?
My intention of highlighting the example above is to drive home the point that most organizations do not even do the most obvious things from a data analysis perspective.
The best way to start Analytics in your organization is to start by asking some simple and obvious questions, both from a shareholder/management point of view as well as from a customer point of view. Once, you have a list of questions and facts that you would like to see, start using the data and see if you can come up with those facts and/or answers to the questions that you have.
The next stage is to convert the facts into reports which can be generated for different time intervals and for different slices and dices of data. When you have done so, you have already started building a BI system in place. Once, you have a set of reports that show important and engaging facts about the business and have insights and answers to questions that any manager would love to know, you have already built a case for yourself to start using Analytics in your work/organization.
4. Make a case study of your work and show case to the top management. Else, add it to your CV. If your organization is not supportive of your Analytics initiative, look outside in the relevant domain. There would be plenty of opportunities outside for a person with your new found skills!
5. Read plenty on Analytics – Join blogs on Analytics, Analytics threads, follow Analytics companies and keep abreast of the latest happenings in Analytics. This will keep you well positioned for keeping a track on how Analytics is being applied in different business domains and functions and increase your knowledge in the field.
Being true to the magic number 5, here are 5 possible career paths that you can chose in Analytics.
1. Tools expert/expert programmer – Experts in programming and nitty-gritty’s of the software. You can become the go to person for any programming related queries and software troubleshooting.
2. Expert Modeller – more often than on, the best programmers are not the best modellers and vice versa. That is perhaps, because you need different kinds of temperaments for these two different skill sets.
3. Solutions Expert – conceptualize and create Analytics solutions to help solve business problems. A Solutions expert understands the problem to be solved and has the expertise in creating the most appropriate Analytical framework to solve the problem. They also recommend the best method/sets of methodologies to be used to solve the problems. They are the “Analytics Architects” if you can call them so.
4. Story Teller – you are able to create the most practical, impactful story that helps clients change their businesses. You have the ability to understand the business of the client, their pain points and pull together insights from the Analysis to weave together powerful strategies for the client.
5. Analytics Salesperson – your job is to convince prospective clients to use analytics in their business and show them how they can benefit.
Let me add a 6th one. Give back to the Analytics community– when you realize that you have learned enough, start dissipating that knowledge to the larger community. The more people become aware of the power of Analytics in career, the more they will adopt it and start using it.