Coding for Consultants
Companies that are frequently associated with coding and programming are tech giants such as Google, Apple, Facebook, Amazon, and Microsoft (GAFAM). However, as companies digitize their businesses there is often more data than can be consumed. This has resulted in coding becoming one of the most important job skills for professionals across many industries including management consultants.
Like GAFAM and major banks, consulting firms have either been building or aggressively expanding their data analytics department. They are seeking individuals who can design algorithms and construct complex models. A dedicated analytics team that works with general consultants to analyze large data has proven to drive business decisions for clients; I have personally found that the ability to analyze data, develop applications, and create tools to enhance a client’s business are skills that are invaluable at many points during client engagements. While I agree that a dedicated analytics team is useful and perhaps essential to being competitive in the industry, I believe that all consultants should have some general knowledge and proficiency in coding.
Data analytics beyond excel
Most generalist consultants neither code in Python or R nor do they use SQL for database management. Fluency in manipulating data on Excel is often the base requirement, but it is time to expand beyond this skill set as the world is becoming faster and more automated. As we know it, automation will have a profound influence on the future of all industries; machines will be able to perform an increasing number of tasks both efficiently and simultaneously, and if consultants are not able to equip themselves with skill sets that support this change, it makes it difficult to truly be effective and provide value to our clients.
Excel has gained extreme popularity since its inception in the 80s and it has become the go-to tool for all types of data analysis. However, many of us do not stop to think whether it is the right tool for the task at hand. While Excel is a great mass-market tool that provides the power of statistical analysis in a relatively user-friendly way, it does not separate the numbers from the process which makes it difficult to follow the logic behind an analysis, find the error, and manipulate a spreadsheet that someone else has created. Furthermore, it can be relatively slow when handling large data sets as many of us know.
That said, my challenge is for consultants who are unfamiliar with Panda and Python or R to learn something new – try to develop a basic understanding of data visualization, statistical analysis, debugging, and commenting on codes using these tools. Learning to code can be intimidating but it is a form of problem-solving that will get better with practice. Finally, while it is up to the individual to be committed to learning something new, I believe that it is worthwhile for consulting firms to invest in their staff by providing the necessary tools and training for coding.
The author of this blog, Kevin Kim is a Senior Consultant at Trindent Consulting