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Email:  info@profitand.com

Profit& Ltd
68 King William Street,
London,
EC4N 7DZ,
United Kingdom

Telephone: +44 1158 943 983

Profit& GmbH
Neuer Wall 75
20354 Hamburg
Germany

Telephone: +49 40 22859120

Profit& Sp. z o.o
Ul. Złota 59
Skylight p. 14
00-120 Warsaw
Poland

Telephone: +44 7818 568970

Finance, FP&A

3. How Machine Learning and Artificial Intelligence Benefit FP&A

Corporate resilience and how to build it was the topic of the first piece in this short series. Then we discussed how important scenario analysis has now become in financial planning and analysis, FP&A, and why it will remain so long after the disruptions of 2020.

One of the characteristics of resilient organisations, is that they typically establish tiered multi-disciplinary teams that are empowered to make rapid decisions, that transcend traditional organisational hierarchies. Such collaboration and corporate agility is clearly best facilitated by adopting cloud-based solutions and in-memory planning platforms, such as that of our software partner Anaplan, that unify previously disparate planning processes around a shared data set to deliver ‘connected planning’ and rapid scenario analysis.  

In recent years, most engagements here at Profit& have been helping organisations deliver this transformation. Typically, clients first address core financial processes to deliver quick wins before addressing other, previously standalone, sales and operational planning processes to deliver an enterprise wide ‘connected planning’ solution.  Once our clients have experienced the benefits of ‘connected planning’ for themselves, many members of their FP&A teams want to know what should come next on the transformation path. Most often the answer is more accurate and robust forecasting, and typically that means beefing up the analytics components of FP&A.

Raising the bar on analytics and forecasting

The most resilient companies are typically early-responders, quickly identifying internal and external micro-trends, that could be the precursors of more significant shifts. They could be small internal micro-trends such as signs that sales of new product are peaking earlier than forecast, or the early warnings signs of seismic shifts in customer preference that, in the past, have brought companies such as Kodak and Nokia to their knees.

Companies have a plethora of internal and external data, so sorting through it to identify exactly what is important and extrapolate meaningful insights that impact forecasts, is both time consuming and something of a black art. To better manage the complexity inherent in its rapidly growing businesses, the technology company Amazon developed sophisticated time-series forecasting methods, that incorporate machine learning and therefore artificial intelligence capabilities. Put simply, the system automatically identifies the most salient data that underpins a forecast and the statistical forecasting method that, over time, produces the most accurate results. Then through repeated reiterations, and by comparing forecasts against actuals, it continually refines the forecasting algorithm to improve accuracy.

Our partner Anaplan has recently packaged this service into Anaplan PlanIQ™ with Amazon Forecast.  This provides platform users with seamlessly integrated machine-based learning forecasting techniques. Rather than simply forecasting a single data set, such as Sales Volume, users can upload other internal and external data sets, such as web traffic and weather, that the system automatically incorporates to refine the forecasting algorithm and improve accuracy, often by as much as 50%. 

Best-of-breed ML forecasting with Anaplan’s leading connected planning capabilities.

Key decision-makers can rely on the capabilities within Anaplan PlanIQ™ with Amazon Forecast, to get a deeper understanding of how micro-trends might quickly develop into significant business drivers, and understand their likely financial impact in “what-if” scenarios.  That’s not to ignore its more everyday use, in improving the accuracy of forecasts in the numerous sales and operational planning, and mainstream financial planning use cases.

Just like the core Anaplan platform, users of Anaplan PlanIQ™ with Amazon Forecast do not need to be seasoned data scientists. It is designed to be just as intuitive to use as the core platform, so that users can configure, deploy, and operate it, easily incorporating very large amounts of both corporate and third-party data into forecasting routines, that can be automated as part of a regular planning process. 

Anaplan PlanIQ™ with Amazon Forecast is a powerful addition to the existing intelligence capabilities of the platform, combining Amazon Forecast’s best-of-breed ML methods with Anaplan’s leading connected planning capabilities.  This greatly enhances ability to deliver forecasts, something that we passionate about at Profit&.  

If you like to learn more about Anaplan PlanIQ™ with Amazon Forecast take a look at the Anaplan Solution Brief.

 

Learn more 

If you’re interested in seeing how Anaplan can increase the efficiency in FP&A, don’t hesitate to contact us.  We’ll be able to answer all of your questions and explain the processes we use to bring cohesion and effectiveness to financial planning and analysis.

Contact Us

Finance FP&A
Steve Benham

Steve Benham

Steve's passion is to help finance departments become genuine business partners, transforming them from corporate historians into fortune tellers, so that CFOs become relied upon for insights into the effect of decisions on future profitability. Steve qualified as an accountant with PwC and spent 15 years of his early career in CFO roles, before forging a career in cost management consulting, spanning over 20 years. Steve has implemented large cost management projects and developed deep expertise in key sectors including Airlines, Utilities and Manufacturing. Prior to establishing Profit& in 2016, Steve was a Director in PwC Finance Consulting and Cost Management Practice Lead in Vantage Performance Solutions. Steve also led Consulting Practices for Cost Management in technology firms including SAP, Business Objects and ALG Software.

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