- As the finance industry goes through digitization, we have to learn how to leverage data.
- Equipped with data analytics expertise, CA Sachin Chitlange is currently driving Finance Transformation at Capgemini India.
- At Capgemini, he was fascinated by the power of data analytics and its ability to help clients.
- You don’t need special skills to be a data analyst. You need to have the right mindset.
Back story: Fascination with technology
After qualifying as a CA in 2000, I started my career with Anand Rathi Securities, a leading full-service securities firm. I was put in charge of handling the portfolio for HNI (High Net-worth Individual) clients and was managing a total of INR 1500 crores of investment every week.
But later I thought “Although it is a flamboyant and glamorous job, it is not my cup of tea anymore.” It was time for me to experiment with my career options (which everyone does early on).
I decided to get into corporate finance. In 2001, I joined Gati, a listed logistics company based in India, as Head of Finance.
In 2004, Gati decided to go ahead with ERP implementation. It was a bold move for an INR 400 crore conservative company. I was made the head of Oracle ERP implementation. And that’s where my fascination with technology started.
In the process of self-discovery, I found that “I should get into finance transformation.”
In 2005 an opportunity from Infosys came. Infosys is a multibillion-dollar IT Company that provides business consulting, information technology, and outsourcing services.
I joined them with the intention of creating solutions for the clients on ERP implementation, and of course to get an opportunity to go abroad. (Most of Infosys’s clients were from the US and UK. Usually, when people join an IT company they aspire to go for onshore work.)
However, when I joined Infosys I was put on a support project, mostly solving tickets for clients that have implemented ERP!
Not exactly my kind of role, but I still put on a smile and gave my best. Soon after I got an opportunity to go to the Middle East.
Needless to say, the client was very happy with my work.
There was no looking back.
Opportunities in Finance Transformation and Analytics
I loved the tech side of my role but was not able to use my knowledge of finance as part of my work.
In 2011, a lot of companies started adopting IFRS, so I decided to pursue a course on the same.
Upon completion of the course, I advised Infosys on how to implement IFRS in Oracle ERP.
After a while, I noticed that many companies were trying to set up HR and financial shared services in India. Capgemini, a global leader in consulting, technology services, and digital transformation was one of them.
Two years later they were looking for somebody with finance and systems knowledge, to handle their shared services team in Pune. That’s how I moved to Capgemini in 2011… And got my finance role back.
At Capgemini’s shared services center, a lot of processes were manual; invoices were managed on an excel sheet. That’s when I brought in my Oracle ERP knowledge to automate all those manual processes; earned a lot of respect from the local team.
Over the years, I helped them with business efficiency, system improvement, and process improvement.
In 2013, I became the Senior Finance Manager and got the responsibility to handle a larger shared services center in Mumbai with a 100 people team.
I was handling transformation projects around P&L, restructuring projects, mergers, and acquisitions, and even implemented SAP-based P2P solutions. I also led Finance Transformation for India and Group, around Finance Processes, ERP, Systems, Acquisitions, Robotics, and Digitization.
All was going smoothly until 2020 came and COVID hit us.
Many clients of Capgemini started worrying, “How will we recover payments from our clients now?” “Will we be able to hire employees in the midst of the COVID-19 pandemic?”
Having led the Finance Transformation for India, we said, “Why don’t we use data to pacify the businesses?”
We looked at the data from the big recession of 2008. We prepared very interesting insights from the data, such as giving X amount of discount to customers to win the deals. This is how you could recover your money.
Nobody told us to do the data analysis, we did it because of our own interests.
We prepared and showed these data analyses to our clients.
Looking at our work, our CEO exclaimed that they want to create a data analytics team. My colleague and I were the ones who made the data talk to solve the problem.
Fast forward to July 2022, I became the Vice President of Business Analytics and Finance Transformation at Capgemini.
In my opinion business forecasting would be the biggest thing that finance controllers should be cognizant of.
Still, many finance professionals use excel sheets for data collaboration and reporting numbers, but most of it will be facilitated through Machine Learning and Artificial Intelligence. The same thing is going to happen with the FP&A function, forecasting, and budgeting.
With most of the manual tasks being automated, finance professionals are going to add value in changing business plans, and working closely with the business as a partner to stay ahead of the competition.
The most important thing is understanding the problem of your client and having a business mindset. Your mindset to understand how data integration happens, and where and how the data is stored.
Then working with the business to resolve that problem by presenting data in the right way. It’s all about understanding the flow of data, and how each piece of data connects with the others. Once you understand this then it’s all about playing with the data.
Today technology is driving business so you need to keep up with the changes. Understand how the finance industry is evolving.
If I could start my career all over I would get into finance transformation from the get-go. And take up a role that revolves around Analytics and MIS reporting.
You don’t need special skills to be a data analyst, it is all about your mindset.
Of course, you need to understand tools like Power BI to get access to different data sets in one place and understand data mining. But these tools can be easily learned.
You could take it up a notch and learn programming languages like SQL, Python, or R, I don’t think it’s necessary but can be helpful.
I don’t call myself a big programmer but I can challenge the techies if they are not picking the data from the right place or if I see something wrong.