John France - Head of Sales Operations & Analytics

Question 1 : How has your role evolved over the past 12-18 months?

My role has evolved by implementing a centralized approach of consolidating business intelligence, sales operations and analytics teams under the same leadership to identify and solve business pain points which include data environments, strategy, innovation, enablement, market insights, and sales optimization.

Question 2 : What advice would you give someone wanting to become a Chief Analytics Officer, and what are the core skills one needs to thrive within the role?

In my opinion there are 4 key skill sets to be successful as a CAO: First, you need to understand the strategic plan of the organization and identify the gaps that may hinder the company’s ability in getting there. Second, formalize an action plan and deliver clear and consistent communications leading your teams and cross-functional teams will be key. Third, continue to deliver value to the business solving current and potential pain points. Fourth, a CAO needs to be driving solutions utilizing data science that will shift into actionable business insights.

Question 3 : Data is exploding, the number of analysts is flattening and expectations and demand are growing – how does one best manage in this scenario? Should the focus be on processes or business problems?

The typical business approach is to analyze every aspect of the business searching for the problems and then try to develop solutions. My opinion, this is a reactive approach that will let your competition get ahead. My expectation is to have my team focus on delivering value to the business by implementing best in class processes and develop innovated tools which then provides ample time to analyze data aligned to our KPI’s to drive performance.

Question 4 : What is the biggest challenge you face within your role today and how are you looking to tackle it?

In my company there are several business units that share key resources. Utilizing this shared resource model, projects become challenged on getting top priority. In addition, these shared resources are unfamiliar with the data structure and/or product of the business unit which can cause delays in developing the BRDs. My approach to work through this challenge is to develop a strategic

plan involving a steering committee which has shared resources as members to partner and prioritize projects. One of the deliverables is to develop a core team that works consistently on my business unit projects to minimize product & data structure education. This will increase the deliverables dates by decreasing ramp up time.

Question 5: What is the biggest challenge faced by the analytics/big data industry currently and in what ways does this affect your business?

My challenge is there are so many products out there now that drive BI, behavior science, master data management, etc… It becomes overwhelming because you are not sure where to start. Therefore, you end up defaulting to your network and asking questions about your challenge and if they know of any good product or approach to solve for it. Another challenge is the integration of these tools into our data structure. Over the years and several acquisitions we now have a “Frankenstein” type of infrastructure. Without a complete overhaul and millions of dollars, we really need tools that are easily bolted on.

Question 6: Where do you see being the biggest area of investment in analytics within your industry over the next 12 months?Since I am in the pharm industry, I think the biggest area of investments will be tracking the physician and patient behavior. Every year there are new products, drugs, regulations, etc… that both the physician & patient community need to be informed on. We are already moving towards EMR (electronic medical records) which is a great thing because now a patient can go to any doctor and have a file electronically of all their diagnoses and treatments including meds. I think the next step is moving towards the predictive modeling phase where physicians are reaching out to patients that fall under a certain criteria for a product that may help with their treatment. For example, if a patient has been diagnosed with prostate cancer and they have had several treatments of certain drugs, then this patient may be suitable for drug that will help them with their quality of life. The physician community can use data science to identify these patients and inform them of a new treatment. Could be life changing!

Question 7: What is the biggest future trend you see within the Big Data and Analytics space? (For example, what opportunities do new data sources such as IoT, web, social, mobile, and ecommerce present? OR What are the future possibilities for Machine Learning, Deep Learning and AI?)

I think the opportunities are limitless. For example, if there was a machine that could scan you at home and provide an instant reading on your health (heart, blood pressure, cholesterol, diet, etc…) and then deliver an action plan to correct such as what to eat that day, a work out regime, what meds to take, etc… that could really help save lives. In addition, provide quality living. Then to really push the future step, once the home machine scanned you it will then create a shopping list for your nutrition, or schedule your physician appt., etc… Essentially providing your action plan by a simple

scan and click of the button.