IBS Intelligence Basel IV Webinar
FinanceMay 08, 2024

AI self-assessment: Can AI help your finance team and CPM processes?

Artificial intelligence (AI) is everywhere — in our homes, phones, and cars — so of course it’s becoming embedded in the software systems that buoy our job functions. For data-driven departments like finance, and data-dependent processes like corporate performance management (CPM), there is no better fit.

AI promises to improve finance’s efficiency, data discovery, forecasting, and analytics. But what does this look like for your specific set of processes?

We created this self-assessment to help you define how AI can augment your CPM processes.

Test 1: Perform an automation gap analysis

An automation gap analysis identifies areas of CPM where AI can augment human effort. Remember: AI should not replace your finance team’s expertise. Instead, it should support teams with advanced automation so that they can focus on the tasks where human intelligence shines: strategic big picture thinking and subjective analysis.

The goal of your automation gap analysis should be to determine your current state and your desired state based on the potential for AI to automate repetitive tasks.

Ask your team:

  • What CPM tasks do they perform that are still manual?
  • What automated CPM tasks do they perform that still consume time?
  • Are those areas critical for performance?
  • Are those areas eligible for improvement?

50% of finance functions are looking to close the gap in their ability to handle data over the next 3 years. - FSN

Test 2:  Quantify time lost to manual tasks

How much time does your team really spend on each CPM task? And what is the ratio of time spent between:

Data management: Data entry, data collection, validation, anomaly detection
Data discovery: Drill down, sourcing information, updating KPIs reports
Analysis: Understanding business drivers, simulating scenarios, and preparing recommendations for leadership

Data collection, verification, and management are critical tasks, but for many teams, it’s more time consuming than it needs to be. One of AI’s biggest strengths is that it can automate and enhance repetitive data processes by learning from the patterns in existing data. Many data management tasks are both repetitive and data-driven — which makes them prime candidates for AI. And manual tasks like data mapping and anomaly detection are ripe for machine improvement.

Task your team:

  • Ask your team to track how much time they spend on the following tasks:
    • Data collection and input
    • Reconciliation
    • Account and transaction
    • Calculations
    • Reporting updates
    • Analysis and data exploration
    • Narrative and comments
    • Disclosure
  • Determine what AI tasks can accelerate. For example: AI in CCH Tagetik automates data verification tasks like anomaly detection, data collection tasks like mapping, and data discovery tasks like business driver analysis.
Welcome AI onto your Finance team
AI-based corporate performance management software helps finance teams make strategic decisions faster.

Test 3: Data source analysis

CPM isn’t an island. Financial processes require data from sources across the organization, including:

  • Finance systems (ERPs, data warehouses, treasury systems)
  • HR systems
  • Supply chain and procurement systems
  • IT systems
  • Real estate systems
  • Vendor systems
  • Market data
  • EHS, carbon, and emissions systems

Data can be financial and non-financial and communicated to finance teams in many ways, including email, IM, verbal, Excel file, reports, or directly into finance systems by ETL. The more data sources that are manually collected and managed, the more room for error emerges. Numbers can easily be keyed incorrectly into financial statements or uploaded with different formats.

Task your team:

  • Ask your team to list the data sources and files they use to complete CPM tasks
  • What are the manual interventions that need to occur with each data set or process:
    • Data collection
    • Validation and verification
    • Reconciliation
    • Calculations
    • Reporting inputs
    • Scenario modelling
    • Forecasting and projections
    • Narrative and comments
    • Analysis
    • Disclosure
  • On a scale of 1-10, how overwhelmed does each team member feel by the volume of data they must manage?

75% of finance organizations experience a material accounting error every month. - FSN

AI is an ally to finance — not a replacement

Now that you’ve completed the self-assessment, you’ve identified areas in your financial processes that could be augmented and improved by AI. Use your findings to prioritize the processes to add AI to first as the basis for an AI transformation action plan

There’s a common concern that adopting AI kicks off a journey of replacing human intelligence with machine intelligence. AI in CCH Tagetik acts as a sidekick to finance teams. It takes care of repetitive data challenges, like data collection and anomaly detection, as well as data discovery, like business driver-analysis, so that finance teams can focus on what they do best: analyzing performance and advising on data-driven decisions.  

If your self-assessment reveals significant automation gaps in your financial operations, it’s time to introduce AI to your CPM platform. Learn more about AI in CCH Tagetik.

Senior Innovation Consultant - CCH® Tagetik

She has been working in CCH Tagetik for about seven years. She was also involved in the analysis, design, and development of Business Intelligence/Advanced Reporting solutions. In recent years, as a member of the Innovation Team, she has been working as Innovation Consultant supporting the application of Machine Learning/AI features to meet customer needs.

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