A Swiss Army Knife for Strategy Planning

October 16th, 2018 by Martin Chan

Solving strategic problems through connecting data from different sources

Last month, I spoke at EARL *, which is an annual conference where data scientists and consultants share their experiences and techniques in using the programming language R in commercial environments. This is one of the largest conferences of its kind in London, attended by almost 300 R users from companies ranging from Microsoft to HSBC, and Marks & Spencer to Dyson.

The talk introduced our work here at Rainmakers CSI, and mainly focused on how we as a consultancy take advantage of programming languages like R and VBA to help us spend less time on repetitive production tasks, and more time on thinking.

There is a twist, however. As brilliant as this idea might sound, it is in fact not as straightforward to achieve in reality. One of the ways we add value to our clients is through piecing together disparate bits of information, such as:

Metaphorically, this is like putting a jigsaw puzzle together, where we take different pieces of puzzle (information) to form a representation of the business landscape, which answers the question of “where are we as a business?”. This picture then enables us to develop highly bespoke, creative, and evidence-based strategic input for our clients. What this also entails is since the work we do is non-formulaic, it is therefore (at first glance) difficult for us to benefit from automation.

This doesn’t necessary mean that we are stuck with old methods of analysis. Instead of seeing R (or whichever analytics tool) as the modus operandi that defines our process, we tend to view and use it like a Swiss Army Knife – i.e. a valuable, multi-purpose tool that comes in when a specific situation calls for it. This includes challenges such as hypothesis exploration and identifying themes from raw unstructured data, where R enables us to create reproducible (re-usable code) analysis that takes less time to produce whilst covering greater breadth and depth. Where applicable, we also use R to help us produce visualisations and web-based dashboards (“Shiny”) to suit specific needs for deliverables. The greatest benefit of R to us therefore is that it enhances the overall quality of our output, and allows us to focus on the meaning and the strategic implications of the analysis.

This is perhaps best summarised with a quote from the presentation:

“Our goal is to provide simple, commercially actionable advice for our clients, and R allows us to carve through a mountain of data from different sources, synthesise the findings, and create something which business stakeholders with different areas of focus can easily understand and act on”

The full slides to our talk at EARL can be downloaded here.

*Short for “Enterprise Applications of the R Language”

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