“The system is not working!”
Who as a finance leader never heard this feedback as one of the reasons why, as usual, closing the books is going to be late? One entity provides late financial information and the entire group face the risk to miss the deadline.
Then days later while reviewing the numbers with your teams, and after several hours of video-conferencing, you conclude that some entities report different numbers (in same GAAP ledgers), and you wonder why the visual dashboards shown are different across entities?
It is now D+20 and your company books do not look straight, forecasts are not aligned. Another rough time ahead on explaining why the finance department is always late…
You think “Why this keep on happening?” You were told to move to the Cloud and you did. You were informed your teams required training and you provided it. You were advised many things, spent a good amount of money but the results do not meet your expectations.
You google some key words and you read “blockchain” “AI” and you feel somewhat dizzy because you realize it is about to become more complex and that lots of challenges are ahead of you.
One of my ex co-workers and friend wrote this excellent article about Data Science and Machine Learning. You may look at it as I believe it is useful to acquire some basics (https://www.linkedin.com/pulse/5-quick-answers-data-science-machine-learning-questions-rameen-rahman/).
Moving to the Cloud seemed like a major accomplishment but it is of no use if you replicated the processes you used before.
Indeed, the future is not on how your reports will look like. The future is about what data you will feed in these reports (well, as it has always been I would say).
“Crap in, crap out” is a well-known expression in the consulting world and the data is one of the keys for the future of efficient and effective reporting. More than ever.
Why?
Firstly, commercially, to align with the market(s). Information about customers, clients, patients, users is essential (this you know).
Secondly, the pressure of governments and authorities (financial, regulatory) who are now very sharp in using cross-referencing technologies (and this one you probably ignored).
Regardless of how fancy the technology you use (even if some reporting tools are very cool to work with – they call them playbooks!), if your data is not well structured, collected, updated and understood across all functions in your company, even artificial intelligence won’t support you.
When I explain Blockchain and AI I use the following :
Blockchain : it is the DNA. The DNA code tells everything about a person. Not only about an arm, a leg or an eye. It is the same for companies.
AI : it is a child made with the DNA. It will require support and education to mature. It will fly with its own wings, but you require a captain and a crew to maintain the direction.
Unlike for the year 2000 bug (Y2K), there is no hard deadline to adopt Blockchain and AI (well lets says predictive analysis). But denying their benefits and obligations would be a terrible mistake which companies would correct at big costs (using the same Big 4 and IT companies who made a lot of good money for Y2K).
My advice is:
1) Do not feel alone. A large majority (70% or more) of the CFOs do not understand blockchain, AI, etc. and are not ready to move in that direction.
2) There is no rush for adoption. Don’t be an early adopter who will fail for others to have success.
3) Design well your plan and follow a rigorous project methodology. Integrate step by step the concepts but keep in mind we are in the era of V4 (and not 4.0 as I was told) and new technologies may influence your original plan.
4) Don’t be wowed by the names of the companies advertising that if you don’t have it now, you will fail. That is not true. Think about electronic signature in 1998-2000 (which is my best example): pen business is still performing very well in 2017!
5) It is not that complex!
And do not hesitate to ask questions and of course like and share this article!
Thanks for your time!
Rui
