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3 Important Steps to Get Ready for Artificial Intelligence and Machine Learning

Apr. 7 2020 by Leslie Cant, Product Marketing Director - CCH Tagetik

Performance Management Business Intelligence & Analytics Budgeting & Planning

Given today’s unprecedented global uncertainty, most of us are wishing we had a crystal ball. How will the economy be impacted? What will my organization look like when this is over? What does my own future hold? It’s impossible to say for certain. When it comes to the future of your business, the closest thing to clairvoyance technology can offer us is AI and machine learning.

The CPM software market has started setting a foundation for artificial intelligence (AI), machine learning (ML), and predictive analytics. For many of us, these technologies sound too futuristic to be true. And yet, AI, ML, and predictive analytics will soon be a common place staples, leveraged by leading and growing companies alike. Mark my words: like automation and double entry logic, they will become the norm in the CPM software world, enabling finance teams to increase their strategic impact in unprecedented ways. After all, knowledge is power — and that’s exactly the promise of AI and ML.

This leads us to our next question.

Is Your Organization Ready to Embrace AI and ML as Status Quo?

My experience based on numerous engagements is that, generally. organizations are not ready for this change. Despite the emerging availability of these powerful functionalities, many companies — perhaps even yours — are still using legacy software that limits their business foresight to basic revenue and expense planning. Translated, this means that on the spectrum of readiness, legacy planning systems relegate companies to the far-end of unprepared. Whether stuck in the muck of managing custom scripts or limited by the bricked in nature of stack products, legacy planning systems lack the functionality and data intelligence today’s planners need to drive their business forward, confidently and competitively. The only thing worse than this predicament would be using a manual spreadsheet-based system — but that’s another topic for another post.

As ML and AI evolve, the question isn’t whether companies will adopt — competitive pressure will dictate that resistance to these technologies is inevitably futile. Instead, the question needs to become: how can organizations ready themselves for adoption without feeling as if they’ve time warped from the stone age to the machine age?

As we recently discussed in our eBook, The Next Evolution of Planning, to get ready for AI and ML, finance must:

1. Move away from legacy planning systems

The first step to bridging the gap is a harsh truth: finance must recognize that legacy planning systems are outdated and no amount of custom scripting or IT add-ons will bring it up to date. Legacy planning software simply cannot handle the data models or depth of analysis needed to manage big data, let alone handle the breadth of data ML and AI demand

2. Understand planning requires complete data mastery

Planning isn’t about historical numbers alone, nor is it just about financial results. It requires data mastery. This is true because, to be effective, machine learning and AI technologies require organizations to increase the quantity of data they are collecting. For planners who aren’t using the right software, this is a contentious issue because of data quality. If machines are fed inaccurate data, erroneous information will seep into the resulting plans and the business decisions that those plans guide.

How can we prevent this from occurring? By mastering unstructured data, centralizing it into one trusted source, and ensuring its quality through automation. Only then will we be able to see the relationship between operational decisions and financial outcomes that planners need to improve their strategic insights.

3. Build a foundation for ML and AI

The key to successful machine learning is providing machines with enough data to learn. Thus, to embrace these AI and ML, you’ll have prepare data for ML and data science, build ML models, acquire domain expertise, and — lest we forget about our compliance requirements for transparency — establish controls throughout the process. You must build a foundation.

Today’s finance teams can begin setting this foundation by choosing technology that promises to grow with AI and ML technology. Open system architecture, a robust data engine like the CCH Tagetik Finance Transformation Platform, powered by the Analytic Information Hub, in-memory processing, and a hub that has the ability to centralize both internal and external data — these are essential first steps towards the future of planning.

AI and ML have the potential to grant Finance the ability to produce insights from unprecedented depths of analysis. By honing these leading-edge technologies, you’ll find you’re able to work in tandem with the office of the CEO, and have a measurable impact on the future of the business — no matter how uncertain the times.

To learn more about the how planning is changing and the planning functions businesses need to adopt to remain competitive, read our eBook: The Next Evolution of Planning.

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