Imagine you’re the CFO of an insurance firm. You’re trying to get a handle on where your profit really comes from. Which policies, products, or sales channels are driving profits and losses? Where are the sources of most of your claims, and how are those impacting profit? How can you get to the underlying financial and operational data that reveals what’s really driving the business?
If you can answer those questions, you can make confident, informed decisions about where to invest in technology and people so as to better adapt to changing market conditions. This is essential to becoming a decision-ready organization. If you can’t answer those questions yet, read on.
Competing in a Data-Saturated World
A big part of becoming decision-ready is harnessing data, but that alone can be challenging. The pace of data growth, for instance, is staggering. Between 2010 and 2020, the amount of data created, captured, and copied grew by 5,000%. And it’s showing no signs of slowing down. By 2025, the world’s population will generate an estimated 483 exabytes of data every day. This accelerating data volume and velocity makes it challenging for companies to manage and make sense of the data they use to run their businesses. And it complicates the ability to define their competitive edge in a rapidly changing, data-saturated world.
Companies struggling to get out from under this data tsunami are slowly sinking. In a 2021 survey of 85 Fortune 1000 companies, a mere 24% defined their business as being data-driven in the last year. And even though demand for highly coveted data scientists is on the rise, turnover is noticeably high. The biggest complaint? Companies haven’t laid the groundwork for success.
Laying the Groundwork to Be a Data-Centric Company
Unfortunately, simply standing up solutions and tacking them on to an existing environment won’t address these shortcomings. Instead, business and finance leaders looking to alter their trajectory by harnessing the power of data need to start at the bottom and work up. Clearing the path forward to a future-proof, decision-ready state hinges on having one place to ingest, enrich, and transform data, all connected to the system of record; in other words, it requires an intelligent data foundation.
A unified, broadly accessible data core is something every successful enterprise must have to succeed if it hopes to modernize finance and the enterprise as a whole. For instance, Deloitte has branded the intelligent data foundation as the “common information model” (CIM). From Deloitte’s perspective, implementing an effective CIM is a prerequisite for organizations aiming to plan, record, report, and measure performance consistently across the enterprise. “A well-developed CIM will create a consistent way to look at data,” notes Katie Glynn, Deloitte senior manager of digital controllership. “And when accountants think about data, we like to think about financial data. But there are also managerial and operational data components that need to be considered to really enable a future vision for finance.”
Deloitte identifies a set of principles that help create a sustainable financial transformation. An effective CIM must be:
Granular. The data must be detailed enough to help enable automation, limit reconciliation, draw insight, make decisions, and generate meaningful reports.
Unique. Each data element has a unique and singular purpose. Avoid overlap or multiple use cases to keep from diluting the data.
Flexible. Create a foundation that can adapt to future changes such as reorganizations, acquisitions, and business changes. Pay close attention to reporting, ensuring that it’s fit to meet current and future demands.
Integrated. Ensure any compliance or company mandates are baked into the intelligent data foundation or CIM. Also consider needs outside of FP&A such as business finance, external reporting, local accounting, and taxes.
Consistent. To drive financial consolidation and comparative analysis, establish consistency across all regions, divisions, and subsidiaries.
Governed. Define guardrails to ensure adherence to policies and mandates, and to prevent “drift” overtime.
Once an intelligent data foundation is established and embraced across financial and nonfinancial departments, organizations can tap into a richer dataset that simplifies workflows throughout accounting and planning, and ultimately helps organizations become decision-ready.
A Planning System With Modern Capabilities
As essential as it is, an intelligent data foundation doesn’t work alone. You need an array of capabilities and technologies to leverage it so you can build (and plan) for the future. They include:
In-memory architecture. When large amounts of data are stored in memory, processing time is dramatically reduced, and the need to run batch processes to get your final financial reports becomes a thing of the past.
Real-time data. An increasingly shifting landscape demands real-time data to accurately assess current conditions and constraints, and allows for informed decision-making and nimble course corrections.
Object data model. To take full advantage of the insights gleaned from your data, you need an object data model rather than a traditional chart of accounts ledger structure. With native dimensionality, you can make use of richer analytics and more versatile and granular reporting capabilities.
Connected security model. Drawing insights and action out of your managerial, operational, and financial data depends on your ability to wrangle it in one place and make it securely accessible across applications.
Artificial intelligence (AI) and machine learning (ML). To help you manage risk, surface anomalies, and make better decisions faster, AI and ML should be baked into your planning solutions.
APIs and integrations. Seamlessly integrate your ecosystem of data sources and enterprise systems for an interconnected environment that works as one.
Understanding, Even Predicting, Your Business
As more finance teams helm the digital transformation of their accounting and FP&A operations, decision-makers are reaping the benefits of implementing an intelligent data foundation coupled with modern capabilities such as powerful enterprise-wide insight, future-focused planning, and agile decision-making. Many of these teams are looking to Workday to make it happen.
Rather than asking customers to create a comprehensive environment by stitching together disparate technology and middleware (not to mention custom programming, which puts ownership further out of finance’s reach), it’s now possible to enable a decision-ready environment via a single system that ingests, enriches, and transforms data into accounting, and then taps that data for advanced analytics and planning. And it’s all done in a way that keeps finance in control.
Stefan Ball, Workday senior solution marketing manager, notes how Workday customers can blend operational workforce and financial data to create an enterprise data hub that finance owns. “We can create accounting from that operational data while maintaining a connection back to the source details,” explains Ball. “All of that is then connected and secured by the security model that already exists in Workday.”