How to do grouping of analytics data?

How do you expand the data analytics/data science offering of a consultancy?

• I am currently located a part of the world where data analytics and data science is very new (i.e. no firms or companies have even put SEO on these keywords.) My current position is to provide data analytics support for a Market Research Firm (the data analytics offering is just me and my part time supervisor), however this is a possibility of me moving into a more project management/data scientist role with another consultancy where I would be working alongside a team of 3 software engineers. My role would be alongside the CIO, expanding the data analytics offering of the company (which at the moment is limited to visualisations.) Does anyone have any advice for this particular situation in which I am "selling" a new paradigm of problem solving? I am also curious to hear any advice on people working with software engineers as a data scientist for the first time.

• Answer:

  When you're trying to sell a data and analytics solution, it can be temping to just talk about all the cool things you can do with data. After all, big data is a "sexy" term in many industries - especially in marketing. But data in and of itself is not a solution to anything. Companies use data to help them make better decisions. Simple micro-level data experiments (such as A/B testing marketing messaging) and macro-level decisions (such as deciding to enter or leave a new market) all can be informed by good use of data. What you are really selling isn't the data itself, you're selling the decisions the data can help people make. If all else fails, show the consultancy and your clients how data can help them make more money or have a bigger impact in the industry. The decision makers in a company don't care how much cool stuff you can do with Python or Hadoop. They want information that helps them make more money for shareholders. The paradigm shift is in how you can use data to benefit shareholders, but ultimately the goal is still to make more money and build a better company. Make your case using evidence showing how data can help them do these two things, and they'll be begging you to expand the analytics offerings of your company.