INTERVIEW: Data management and analytics sounds excruciatingly complicated and it is sometimes difficult to get non-technical people to buy into a project. The trick very often, however, is to keep things simple.
The volume of data being captured today by travel companies is astounding. New data sources are becoming available that did not exist before and firms are actively looking at making the most this to solve business problems and get to know their customers better.To do this they need to make sense of the data and align across all relevant business units.
EyeforTravel’s Ritesh Gupta talks to Bill Franks, chief analytics officer and Paul Barsch, products & services marketing at Teradata about big data, the role of specialists in this arena and about how to go about aligning analytic resources for maximum business benefit.
EFT: Who exactly is an analytic professional - a data scientist, predictive modeler or data miner? And what do they actually do?
BF: All of these titles are common for analytic professionals. The new community of data scientists isn’t too different from the community of traditional analysts. They are all focused on finding new and useful ways to leverage data to solve business problems. Any great analytic professional, no matter his or her current title, will have no problem picking up a new programming language or tool, and will jump at the chance to learn about a new data source and now it can be applied. Likewise, if an analytic professional understands how to apply analytics in one industry, it is easy to learn new terminology or compute somewhat different metrics that may be required in one industry over another.
EFT: What qualities should one look for in an analytics professional?
BF: Common technical and educational requirements are a starting point, not an end point. The best analytic professionals have not only the technical knowledge and skills, but as I talk about in my book, Taming the Big Data Tidal Wave, they also have commitment, business savvy, creativity, presentation and communications skills, and intuition. These softer skills are often underrated, but they are necessary because at least half of the perceived success or failure of projects will be how analytic professionals present and position their results to non-technical project sponsors.
EFT: What are the core components of an analytics division within a company?
BF: The key is to align analytic resources so that the various business units in need of analytical support get what is required while the company maintains some type of enterprise consistency.
There are three primary structures – decentralised/ functional, centralised, and hybrid.And there are advantages and disadvantages to each.
Frequently, companies start with a decentralised structure because one particular group, such as marketing, needs analytic resources and those people then report through the marketing business unit. Over time as more business units need analytics support, a centralised structure evolves where one analytic team supports all the various business units.
A common hybrid model consists of a centralised core team, sometimes called a Centre of Excellence, where analytic professionals are tasked with maintaining an enterprise view, along with analytic talent that is embedded within the various business units.
What is most important is that you have the right people doing the right analytics for the right reasons. It is also important to focus on creating an environment and culture that allows the company to hire, grow and retain the right analytics talent.
EFT: Demand on data is increasing and the use of it is also a complex business. What major challenges do organisations face in today’s environment?
BF: One of the biggest trends today is around big data.
Many new data sources are becoming available that differ from many historical data sources. They are larger, often unstructured, and usually contain information that was not available to organisations in the past. Examples include social media data, sensor data, web log data, among others. This trend is necessitating the development of new tools and techniques to handle both the volume and complexity of the data so that it can be effectively analysed. Organisations are finding it a challenge to adapt.
EFT: When it comes to structured data, unstructured data and information management what are the main issues to address?
PB: Unstructured or structured, first make sure that you define a business case for your analytics project. Clearly define your challenge, decide if/ how analytics can help and then build a business case based on revenue enhancement, cost reduction, productivity increases etc.
Second, don’t try and boil the ocean. Pick a business problem that can be addressed within a specific timeframe (ie 3-6 months). Get quick wins to prove the value of analytics.
Third, you will need a firm commitment to data management and analytics. Too many companies have failed implementing analytics because it seemed like a good idea, or because competitors started their own projects. These are not reasons to implement analytics. You will need a firm understanding of your business problem, potential solutions and then map out an achievable plan to get to business results.
EFT: Can you recommend some dos and don’ts for data analytics?
BF: Let’s focus on three dos and three don’ts.
• Do clearly define a business problem before starting an analysis.
• Do focus on improving business decisions through analytics as opposed to focusing on the perfect answer that may never be found.
• Do plan up front how the results of an analysis will be effectively deployed to decision makers.
• Don’t forget to focus on explaining the business implications of findings, not just the technical details.
• Don’tforget to validate the assumptions being made about the data being utilised.
• Don’tmake an analysis more complex than it has to be. Simple is often best.
To find out more about how big data can help you get ahead join EyeforTravel in New York from January 17-18for the Smart Analytics Travel Show .