Month: June 2016

My First Job in Analytics – A Walk Down Memory Lane….



My first industry job, I worked as a Biostatistician at the National Health & Medical Research Council at the Clinical Trials Centre in Australia. The work was very challenging as I was working with real data, and even more stressful, I was working with patient data.

As a Biostatistician, I had to work closely with the oncologists, surgeons and doctors, and determine the Statistical Analysis Plan for the Clinical Trial. Will the Trial be a Double Blinded or Triple Arm Study, Will a Placebo be used, How many patients do we need on the trial, What are the inclusion and exclusion criteria, When will we stop the trial, etc. All these questions were answered using rigorous statistical techniques based on clinical knowledge and historical study results.

I would often share my solution with my manager, Val Gebski, who too often challenged my solution by throwing a lot of “what if” scenarios and getting me to think on several possible outcomes. We often spoke and debated for hours, sometimes the whole day, about different approaches that could be taken.

I remember some nights, in the middle of my sleep, I would get up to write out a method to use the next day to justify my solution. And, first thing in the morning I would run my method on some data and be very excited when the results agree with the typical method and in this way validates our new innovative approach.

I have many examples that I can share but I would say that problem solving is what I enjoy as it challenges me to think of new methods on how to approach a given problem.

I strongly believe and have seen that statistical/analytical techniques are powerful in producing repeatable and consistent results that are accurate when validated and, in a nut shell, Analytics is all about understanding a problem, understanding the relevant data that can help you solve the problem, asking lots of questions and then applying statistical/analytical techniques to make comparisons, predictions and finally optimizing your solution.

How Did I Start My Career in Analytics?



People often ask me, “How did I start my career in Analytics?”. It was actually, quite by accident. In my first year at university I wanted to do the key science subjects such as Mathematics, Physics, & Chemistry but I needed a fourth subject and based on my time table options, Statistics was the only science course available for me. I had no idea what Statistics was about but I fully believed in myself that I could do it, even though there were many stories that Statistics is not easy to pass and the pass rate was only 40%.

I quite enjoyed the Statistics lectures and my professor, Prof Calitz told interesting stories and often challenged us with tricky problem solving questions. I worked hard at solving these problems and often went to my professor to share my solution and ask questions.

Prof Calitz never gave me a straight answer, he always rather probed me with one question after the next and sent me back to complete my solution. At that time, I thought Prof Calitz was a hard man and not very helpful but looking back, I can say that it is through him that I now have a good knack of asking lots of questions while problem solving. And you know what, during my university studies I had to work hard at my other courses such as Mathematics but didn’t really open a book for Statistics and still passed it with a Distinction!

I am today, very passionate about Analytics and enjoy working through business problems, which are quite challenging and more complex.I am very thankful to Prof Calitz for his good teaching approach!

5 Tips for Building a Powerful Dynamic Customer Analytics System


  1. Ask the right questions to achieve your business objective:Begin with the end in mind when asking questions, gain clarity and focus on what you need to know to achieve your objectives. If our goal is to increase our product sales to achieve a financial return of 80% say, To gain clarity we need to ask ourselves the typical 5 questions: Who?, What?, Where, How? Why. For example, who is buying our products, what products are they buying from us, where are they buying (which geography)? How are they buying our products (which channels are they using)? Why did they buy our products?Brainstorm with “what if” scenarios. Understand what the best case could be in terms of product sales, what could be the most likely case and what could be the worst case.

    Companies across industries are trying to understand and connect to the consumer at a more personalized level.There has been a strong shift from the business-to-business (B2B) model to the business-to-consumer (B2C) model.

2. Track the Metrics crucial for your organisation – Use industry KPIs

A good metric/KPI is:

  • A number that drives change you are looking for
  • A good metric is comparative
  • A good metric is understandable
  • A good metric is a ratio or rate
  • Quantitative
  • Actionable
  • Leading Metrics
  • Causal Metric

Below are some examples of good KPIs:

  1. Sales Growth 
  2. Leads 
  3. Customer Lifetime Value (CLV) 
  4. Cost of Customer Acquisition (COCA) 
  5. Website Traffic to Website Lead Ratio


3.Count People and number of unique Visitors instead of:

  • Number of Hits
  • Number of Page Views
  • Number of Visits.
  • Number of Downloads


4. Ensure that your Dynamic System is Data Driven:

To develop a Dynamic Data System, you need the right ‘People’, Processes’ and ‘Technology’.

The key people for a dynamic system is firstly, a Domain Knowledge person – understand the business and data available for answering the business questions,

Secondly, you need a Statistician who understands the statistical techniques that need to be applied to the data to discover insights and patterns that help to solve the business problems. The statistician is also able to provide data visualisation fast using drag and drop type tools for visualisation (Tableau, QlikView, SAS or R) to help the business user to make valuable decisions.

The third person you need is an Information Technology Specialist who ensures that the data definitions are consistent and that all the data is in one place and easy to retrieve for analysis in real-time thereby providing and effective enterprise dynamic system.

For Processes, we need to ensure that we have the right processes in place and that they are continuously improved, which means, we need to track process time and ensure that they are reasonable or even aim to shorten process times.We need to track customer complaints to better understand which processes require improvements and remove the processes that are not necessary.

5. To get the Dynamic System Right – Ask Lots of Questions

Starting with a clear objective is essential and then we still need to ask lots of questions once we have identified the objective. Question such as,  ‘What do you want to Achieve?’, ‘New Customers?’ or ‘Increased Customer Loyalty’ or ‘Increased Revenue?’. Then for example, how will you get the increased revenue? Will you run a promotion? How much increased sales do you expect from the promotion? Which customers are likely to buy from that promotion? When will these customers buy? How will they buy and which stores will they buy from? All these questions can be answered using statistical modelling and classification techniques that can be linked from one to another and in real-time the promotional offer is made to the right customer at the right time with the right product.