Over the last few decades, the role of the CFO has undergone a profound shift. The historical tasks of the finance function including recording transactions, accounting, financial reporting, and statutory compliance continue to be important but are now taken for granted by CEOs. The CFO of today and the future must be able to take financial data and use it to influence operational decision making and strategy. 

Data is king. And it always will be. However, the power to wield the data as a powerful weapon is what differentiates a mediocre company from a great one. If data is not understood properly, it affects everything –  from the products that are being built to the way in which it is being marketed. Furthermore, not having a good hold on the data will result in tremendous loss of capital. One common way of the loss of capital occurs during marketing a product which lacks a proper market fit in the first place.

Over the last decade, companies have had to deal with a lot more data than ever before. With more data and process gaps introduced with use of more and more applications to handle this data, the historical tasks have become far more complex. Just to record transactions, account them and report them, you need far more finance professionals skilled not only in finance as a function but also in understanding the data and processing the data.

At the same time, it is the same data that needs to be looked at from a different perspective to arrive at strategies that can push the company forward at a fast pace. The trick is in separating the chaff from the grain, processing the high quality grain and providing a timely response so as to help the company make good business decisions. 

All this begs the question, How can we accomplish this? 

It definitely needs a new approach. A new way of working that can help quickly make sense of the data that arrives, forecast what will happen over a period of time and take the right decisions to accomplish the goal fast and efficiently. 

Currently, almost everywhere, accounting is done in the following manner. – RECORD, ACCOUNT & ANALYSE. 

  1. Huge amounts of transactions are being recorded manually or in a semi automated manner. 
  2. Accounting entries are made in the books again in a manual or semi automated manner for these transactions. 
  3. Only after this, the transactions are analysed and reconciled. 
  4. Based on the reconciled data, accounting entries again need to be entered in the books and this time it is predominantly manual.
  5. At the time of book closure, more accounting entries are made to ensure that the recorded data aligns with the company’s actual financial position. And again these are manual. Once done this data is downloaded or transferred into another system for performance analysis. 
  6. For the Performance analysis  to be performed, the accounting ledgers need to be mapped to the MIS groups and sub groups so that the data can be transformed to reflect the right reporting metrics. Now another area of concern here is that the accuracy of the data that gets affected due to gaps in the process done manually. 
  7. Decisions are made based on the metrics calculated during the performance analysis. As this is not real time, the decisions are almost always delayed. 
  8. The risks are identified at this stage. However, this results in delayed optimization which not only results in a waste of effort but improper management decisions. 
  9. The delayed optimization results in a slower growth for the company. 
The issues with this approach are the following:
  1. Decreased accuracy : Manual tasks decrease the accuracy across the entire process leading to increased risk. 
  2. Stressed workforce : Excessive manual work stresses out the team and ties them down with unnecessary work. 
  3. Low skilled workforce :  Highly skilled workers end up wasting time which would be used in a more creative and better way. This will also result in a poor, low skilled workforce over a period of time. 
  4. Delayed Decisions – Slow/No/De-Growth : When analysis on which decisions are made is done post period end, decisions tend to be taken much later than it should have been taken to effect maximum impact. 
  5. Poor time management for the CFO : The CFO who needs to take part in strategy ends up wasting time with the issues related to manual accounting. 
All the above factors enhance the risk at every stage directly affecting the bottom line of the company.  However, Consider this new approach – RECORD but ANALYSE before ACCOUNTING.
  1. Huge amounts of transactions are being recorded in an automated fashion.
  2. The analysis and reconciliation of these transactions are automated, thus resulting in high accuracy and increased speed of analysis. 
  3. The entry in the books is based on the truth only once. Automation of mundane activities relieves the team to concentrate on identification of the root causes, analysis and mitigation of risks, thus resulting in a better managed process. 
  4. With accounting automated and in real-time, faster closure of books.
  5. The performance analysis is available in realtime, anytime as the same data used for accounting is engineered automatically to be also available for analysis. No more transformation of Ledgers to Information groupings needed for performance analysis manually. 
  6. Decisions can be made quicker and in real time based on true state of the performance and the analysis done above. 
  7. Process optimization due to the better root cause analysis, analysis and management of risks resulting in faster growth. 
The new approach results in 
  1. Automation of manual processes reducing a whole lot of time and effort from the finance teams and Increasing the speed tremendously on Action. 
  2. Better and timely management decisions : With the workforce and the CFO freed of the manual accounting and reconciliation, they can concentrate on helping take better strategic decisions for the company. 
  3. Better skilled workforce : The time saved by automation can be used to increase the skill of the workers resulting in a high quality, highly skilled workforce concentrating on critical and creative tasks. 
The earlier approach was an approach that in the past had worked well as the data was less and the complexity was less. Today with huge volumes of data, complex business processes in vogue and data across discrete systems across the enterprise, the new approach makes a lot of sense. Also with the advent of newer technologies and AI, the challenges mentioned above can also be solved.  We, @ DataTwin believe that this is the right time to move away from the traditional approach and through automation and analytics ensure low risk but fast success. 
Subscribe for Updates

Similar Blogs

Scroll to Top