6 Key Questions Finance Leaders Are Asking About Data and Analytics

Better data delivers better insights. As a finance leader, your role is central to identifying and curating the data most critical for company-wide performance. Ensuring data is high-quality, easily accessible, and consistently reviewed lays the groundwork for sound data governance, effective business planning, and dynamic forecasting. However, navigating the complexities of modern data management is no small feat, and finance leaders are often left with essential questions that need answering to drive their organization forward in various critical areas.

To help you address these challenges and capitalize on the opportunities they present, we've compiled a list of six key questions finance leaders are asking about data and analytics. These questions and answers will help guide you in harnessing the power of your data to enhance decision making, drive strategic initiatives, and position your organization for success across data governance, business planning, forecasting and reporting.

1 | How should finance facilitate data governance, and why is it critical?

Answer: Data governance is foundational to effective decision making and strategic planning. It involves creating and maintaining a consistent framework for data quality, helping ensure that all data across the organization is accurate, complete, and up to date. For finance leaders, facilitating data governance means leading the initiative to integrate data from various systems—such as financial, HR, and operational platforms—to create a single source of truth for business planning and analysis.

Why is this critical?

Data Integrity: High-quality data builds the trust and reliability needed for accurate financial analysis and reporting.
Regulatory Compliance: Accurate and appropriately governed data reduces the risk of compliance issues and helps to ensure adherence to regulatory requirements.
Decision Making: Consistent, integrated data allows for quicker and more precise strategic decisions, which is vital in a fast-paced business environment.
Enhanced Financial Analysis and Prediction: A robust data governance framework enables finance leaders to analyze, explain, and predict financial results with higher accuracy. Better data and design facilitate tracing costs from financial reports back to individual transactions or drivers, providing clarity on how and why financial metrics have changed. This level of detail empowers businesses to understand true business dynamics without getting bogged down by data inconsistencies.

Finance plays a key role in data governance because it inherently works across multiple functions, making it well-positioned to drive alignment of data governance policies and practices. Establishing a centralized data repository ensures that critical data is uniformly managed and easily accessible to the business. With efficient access to reliable data, finance teams can deliver deeper insights and maintain the agility needed to respond to evolving business needs efficiently.

2 | How do I get the entire organization aligned with data management?

Answer: Achieving organizational alignment on data management requires a structured and systematic approach:

Appoint Global Process Owners: Designate individuals responsible for managing and overseeing the quality and consistency of data in their respective domains. These owners ensure that data standards are upheld across all functions and processes.
Implement Master Data Management (MDM) Systems: MDM systems integrate data from diverse sources, standardizing and centralizing it to ensure uniformity. This not only reduces redundancy but also enhances data accessibility and usability.
Create Business-Ready Data Sets: Develop data sets tailored to different business functions, such as sales, operations, and finance. This makes relevant data readily available, eliminating the need for extensive data hunting, thus increasing efficiency.
Centralize Reporting Systems: By centralizing finance reporting systems, allow for self-service data access, ensuring that all stakeholders can retrieve the data they need without waiting for approval or assistance. This not only saves time but also empowers functions to make data-driven decisions.
Integrate AI and Automation: AI can streamline the data management process by identifying patterns and anomalies, reducing errors, and ensuring data health. Centralized data repositories with AI capabilities, such as Google , BigQuery, or Microsoft Azure Synapse Analytics, enhance the accuracy and efficiency of automated reporting and accounting.

3 | How can I help my organization adapt to a more volatile business environment?

Answer: Adapting to volatility is about building resilience and flexibility in your business planning processes. Here’s how:

Embrace Agile Methodologies: Implement agile planning frameworks leveraging driver-based planning that allow your team to respond quickly to changes in the market or business environment. This involves short planning cycles and the flexibility to pivot as needed.
Leverage Real-Time Data Feeds: Use continuous and consistently integrated data streams to provide up-to-the-minute insights. This ensures decision makers have access to the latest information, allowing for timely and informed decisions.
Invest in Predictive Analytics: Predictive analytics tools can forecast potential scenarios, helping your organization prepare for different possibilities. This proactive approach reduces the impact of unexpected changes.
Focus on Workforce Reskilling: Transition your workforce from manual data handling to more strategic, value-added activities. This not only enhances productivity but also ensures that your team is equipped to handle new technologies and processes.

4 | How can my finance team become a more impactful business partner?

Answer: Becoming an impactful business partner requires finance to take on a more strategic, forward-thinking role. Here’s what you can do:

Define Data Requirements Clearly: Outline the data needed to drive key business decisions and meet reporting requirements. Be specific about the metrics and KPIs that matter most.
Lead Data Integration Efforts: Work closely with IT and other functions to integrate data systems, ensuring that data flows seamlessly across the organization. This reduces silos and promotes a holistic view of organizational performance.
Adopt Business-Ready Data Sets and Data Products: Develop and provide tailored data sets and data products for different business functions. Data sets should be curated collections of data specifically designed to meet the needs of various stakeholders, making it easy to use and understand. Data products, which evolve from these data sets, are extensive data assets refined for specific business purposes. They are actively managed from definition through retirement, ensuring they deliver high-fidelity and trusted insights. By reusing these products across multiple scenarios, their value increases, and they become essential tools for decision making. Integrating data sets and data products will empower stakeholders to make informed, data-driven decisions quickly and effectively.
Promote a Culture of Data-Driven Decision Making: Encourage other departments to rely on data for their strategic decisions. Offer training and resources to enhance their data literacy, positioning finance as the go-to partner for insights and analytics.

5 | How can I get my business planning and forecasting to move faster?

Answer: To speed up your planning and forecasting processes, focus on synchronization and automation:

Implement Continuous Planning Cycles: Move away from static, annual planning cycles to a more dynamic, continuous planning model. This allows for ongoing adjustments and real-time updates.
Synchronize Upstream Data: Ensure that all upstream data sources feed into your planning systems consistently and accurately. This involves setting up automated data feeds from your ERP, CRM, and other core systems.
Leverage Advanced Analytics: Utilize AI and predictive analytics to automate parts of the planning process. These tools can identify trends, flag anomalies, and provide insights faster than manual analysis.

6 | What new capabilities, technologies, and process upgrades will make our forecasting more dynamic?

Answer: To enhance your forecasting capabilities, consider the following technologies and processes:

Master Data Management Systems: These systems ensure that data is standardized and consistently defined, making it easier to manage and use.
Data Lakes and Warehouses: Create centralized repositories for all your data. Data lakes and warehouses store vast amounts of raw data and make it accessible for various analytical needs, including based on business-ready data sets.
AI-Driven Analytics: Implement AI tools that offer predictive insights, identify data anomalies, and automate repetitive tasks.
Automated Data Feeds: Ensure that your data consistently flows from source systems into your planning and forecasting tools. Automation reduces the risk of errors and accelerates data availability.
Real-Time Data Integration: Integrate systems to provide real-time data updates. This enables continuous forecasting and dynamic adjustments based on the latest information.

Organizations seeking to effectively manage and utilize their data for success must centralize data governance, enhance agility through real-time insights, and use advanced forecasting tools. Finance leaders are crucial in these processes, ensuring efficient, accurate, and strategic decision making through centralized data management and AI-enabled analytics.

Building a structured data strategy, embracing agility, and using the right technologies will position your organization to make smarter business decisions faster. With finance leading the way and KPMG LLP as your trusted advisor, you can navigate the complexities of the modern business environment more successfully.

So, take charge and let your finance team lead the transformation toward a data-driven future.

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