Big Data is the new buzz word nowadays. Its all about analytics and data. But analytics is nothing new in finance. Finance has always been about data, numbers, trends and analysis . In other words, finance has always been trying to tell a story from the numbers.
These numbers have been static and based on a set of accounts , statements and records for a certain numbers of years or months . These are then used to develop insights into trends so as to predict the future performance . Additional variables of market performance , survey insights, currency expectations , consumer sentiment and economic indicators etc are added to help understand the impact of such factors as well as improve the forecast of future performance. This is a static way of doing financial planning and analysis.
The difference today is that the amount of data being generated and recorded is growing immensely and dynamically. Data was always being created but today their is a way that we can record and make it available very quickly and in some circumstances instantly. Financial planning and analysis faces a huge challenge in how to incorporate this changing data into the traditional cycles of annual budgeting, monthly forecasting and even long range planning. Here are the 5 main challenges that I believe faces traditional FP&A:
1) Incorporate existing / legacy ERP systems with dynamically changing data/ information
2) Change current processes for budgeting and forecasting
3) Make data managers and data scientists part of traditional finance functions
4) Compliance / GAAP/ IFRS - Finance still has to be the gatekeeper
5) Training and change management
What are the other challenges that you foresee that corporations are facing / will face in this area?
These numbers have been static and based on a set of accounts , statements and records for a certain numbers of years or months . These are then used to develop insights into trends so as to predict the future performance . Additional variables of market performance , survey insights, currency expectations , consumer sentiment and economic indicators etc are added to help understand the impact of such factors as well as improve the forecast of future performance. This is a static way of doing financial planning and analysis.
The difference today is that the amount of data being generated and recorded is growing immensely and dynamically. Data was always being created but today their is a way that we can record and make it available very quickly and in some circumstances instantly. Financial planning and analysis faces a huge challenge in how to incorporate this changing data into the traditional cycles of annual budgeting, monthly forecasting and even long range planning. Here are the 5 main challenges that I believe faces traditional FP&A:
1) Incorporate existing / legacy ERP systems with dynamically changing data/ information
2) Change current processes for budgeting and forecasting
3) Make data managers and data scientists part of traditional finance functions
4) Compliance / GAAP/ IFRS - Finance still has to be the gatekeeper
5) Training and change management
What are the other challenges that you foresee that corporations are facing / will face in this area?
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