AI can improve data collection
www.freepik.com

AI can improve data collection

Teaser: Gathering data for FP&A using artificial intelligence takes good management and understanding, but as it learns, its accuracy continuously improves.


This is the newsletter "Here's the Future of FP&A and Business Partnering" which has 71,000+ subscribers. You can subscribe as well to receive new articles straight in your inbox every Monday and the occasional Saturday.

The latest episode of The Softer Side of Finance Podcast is live.?Catch it here!

Catch the latest episode of the?#FinanceMaster?Podcast here.

Listen to The Softer Side of Finance today at 15:30 CEST.?Sign up here.

Listen to the?#FinanceMaster?Show on Thursday at 15:00 CEST.?Sign up here.

Brought to you always by?Business Partnering Institute.


Collecting financial data from non-financial people has its challenges, but accounting systems are learning to make life easier. Where once small firm accountants waited in trepidation for the trader’s brown bag of receipts to make up the books, now the same trader is using a simple app to scan their receipts. They are read and interpreted by AI and the details are posted to the right place in the ledger.

This same technology helps enterprise-level input from operational divisions, with machine learning within ERP systems ensuring that transactions are treated consistently and logically. Autocomplete, the AI’s assumption of the most likely next word in the phrase, helps with good annotation. Voice recognition technologies and language prompts allow people to provide the data that’s needed without moving out of their comfort zone.

Applications like ChatGPT can also help with communication. This is a great tool to simplify language, cutting through the jargon so that peers in other functions understand what’s needed and provide the right data for decision-making.

The computer isn’t always right

The FP&A leader still has to manage their AI team member. The computer is not always right, and understanding how AI interprets information is essential in maximizing its effectiveness and avoiding errors.

Autocomplete, like ChatGPT, works on the principle of “what’s the most likely next word”. It draws from the data that it has, and in a closed system like finance, it can be very accurate as it learns it has a limited range of options. Out in the wild, it draws on far more data and takes time to be trained.

Voice recognition is one particular area of AI that is fraught with problems. Research shows that spoken English words that recur in data sets, like date or time, have an error rate under 5%, but AI struggles with non-native speakers, regional accents, and less common languages because there are not enough hours of voice recordings to train the machine effectively.

The names of organizations and people are a particular challenge. As the data sets get smaller, errors rise to the point where it’s really just guesswork. If you’re collecting data using voice systems, manage it with care.

A system that works perfectly at the head office where the AI is trained to recognize local voices will not be as accurate when it’s rolled out to multinational locations. Errors in collection and labeling perpetuate the problem of poor data, and before you know it, you’re making the wrong decisions.

Managing effective AI data collection

Human oversight - good team member management - is important. While AI can be trained to collect data autonomously, human oversight ensures that the data being collected is ethical, unbiased, and complies with relevant regulations. AI can be trained to collect good data in several ways.

  • Data labeling: Data should be annotated or classified according to specific categories or attributes that are relevant to the task the AI is being trained for, so it can learn to recognize patterns and make accurate predictions.
  • Quality control: Verifying data sources, checking for errors, and ensuring that the data is consistent across different sources improves long-term quality.
  • Feedback loops: AI can be trained to learn from feedback, both positive and negative. By providing feedback on the accuracy of the data collected, the AI can learn to adjust its algorithms and improve the quality of the data it collects.
  • Continuous learning: AI can be trained to continually learn and adapt to new data as it becomes available. This means that the AI can improve its accuracy over time by incorporating new data and adjusting its algorithms accordingly.

Do you know which of your systems already use AI to capture data? How do you ensure that the data collection is effective and accurate? Let us know in the comments.


This was the third article in our latest series about the use of artificial intelligence in FP&A. Subscribe to catch the upcoming articles and read the previous ones below.

An artificial intelligence on the FP&A team

Your AI is only as good as its data set

Keep reading to catch our full previous series "It's time to fix management reporting" below.

It's time we fix management reporting once and for all

Here are eight steps to transforming your management report

What are the key messages in your management report?

How to build great slides for a finance presentation

How to structure your management reporting for maximum impact

The slideless monthly management meeting - do you dare?

Don't forget to check out our series "Building the FP&A team of the future". You can read all the articles below.

The FP&A team of the future

The key roles you need on your FP&A team

Re-inventing the modern FP&A leader

How to assess if your FP&A team is fit-for-purpose

How to recruit stellar FP&A professionals

How to boost collaboration in your FP&A team

Branding your FP&A team toward the business

Building a diverse FP&A team

Are you ready to build a world-class FP&A team?

Developing the potential of FP&A teams

You can read a lot more articles about FP&A, Business Partnering, and Finance Transformation below. It all start's with “Introducing The Finance Transformation Nine Box”?where you set the ambition for your transformation. You should join the?Finance Business Partner Forum,?which is part of the Business Partnering Institute's online community.

Great planners always plan with contingencies?(the latest article in my series about the ten commandments of planning and forecasting)

Can't help falling in love FP&A?(the last article in my series about charting the course for a successful FP&A career)

Can we trust the machine for financial planning and analysis??(the last article in my series "Planning (as we know it) is dead")

The secret sauce of FP&A transformation?(the last article in the series "FP&A Transformation Talks")

How Finance should use its seat at the table?(the last article in the series "The Unfair Advantage of Finance")

The ultimate guide to decision-making for finance professionals?(the last article in a series about the decision-making process and how Finance should impact it)

The Mindset Change Checklist For Finance Professionals?(the last article in a series about the mindset change that finance and accounting professionals should make to become business partners)

It's Time To Decide If You Want To Be A Business Partner?(the last article in a series about the personality traits of business partners)

All Successful Business Partners Are "Leaders"?(the last article in the series about our new capability model)

Should We Keep Talking About Business Partnering??(part of a 17-article series where we deep-dive into the WHY, WHAT, and HOW of business partnering by putting it on a formula)

Your Journey To Successful Business Partnering Explained

How To Create Value Through Business Partnering

Everyone Can Adopt A Business Partnering Mindset?(part of a six-article series about FP&A Business Partnering)

From Business Partner To Working Within The Business?(part of an article series where I interview finance professionals about their careers in FP&A and Business Partnering)

Is Your Product Optimized For Value Creation??(part of a toolbox series where we look at what tools FP&A professionals should leverage to drive value creation)

How Business Partners Turn Analysis To Insight?(part of a case study series where I interview business partners about how they drive value creation using real cases)

The Future Of FP&A: Two Ways To Take The Reins

What Is The Accounting Profession Paradox?

What Defines A Finance Master?

The New Career Path For Finance Professionals

How Finance People Can Be More Successful

The CFOs Roadmap To Transforming Finance

How To Become A Finance Business Partner

Financial Analyst vs. Finance Business Partner

Finance Business Partner Is A Bullshit Job

How Business Partners Keep A Plan On Track

Anders Liu-Lindberg?is the co-founder and a partner at?Business Partnering Institute?and the owner of the largest?group dedicated to Finance Business Partnering?on LinkedIn with more than 11,000 members. I have ten years of experience as a business partner at the global transport and logistics company?Maersk. I am the co-author of the book “Create Value as a Finance Business Partner” and a?long-time Finance Blogger?on LinkedIn with 190,000+ followers and 255,000+ subscribers to my blog. I am also an advisory board member at?Born Capital?where I help identify and grow the next big thing in?#CFOTech.?Finally, I'm a member of the board of directors at?PACE - Profitability Analytics Center of Excellence?where I support the development of new analytics frameworks that can improve profitability in companies around the world.

Leonard Schokker

Available | Senior Business Controller | Finance Business Partner | FP&A | Insurance | Banking | Asset Management | Real Estate

1 年

I’d say all data collection has its challenges rather than stressing a divide between finance and non finance. Otherwise great point to look at the added value AI can provide.

回复
Christopher Argent

I lead a forward-thinking, innovative leadership community dedicated to revolutionising the finance function in the digital era. Its members are catalysts for change within the profession, whom we connect & celebrate!

1 年

Great shout @anders

Rajul Kambli , MBA, CMA, CISA, CS

Senior Finance Leader | CFO| Ex. Cornell Alumnus |Head of Finance | Digital Transformation | Global Accounting| Shared Services | Process Improvement

1 年

Anders, very relevant facts on Data and AI. From my experience, I have come across data being captured to see the Operating time of an equipment vs. Idle time. The anlaysis on these, which were more accurate had been far reaching. Time to plan and required for maintenance, How to price your tenders based on historical operating time for operating rate vs. standard lease per month. The same set of information can pivot and help organizations in many different ways.

Nancy Ambrose

Helping Finance Professionals Build Confidence, Ace Interviews & Communicate with Impact | 4+ Years of Empowering Careers Through Expert Coaching | 12 Years as an Accountant Turned English Coach

1 年

Great article Anders. Using the tools available is great in getting tasks done faster but as mentioned you have to check and be sure the data provided is accurate :)

要查看或添加评论,请登录

社区洞察

其他会员也浏览了