It’s rare to find someone in a finance organization who doesn’t believe in the value of analytics, where numbers and the stories they tell come first, last, and always. Yet, the practice of deploying an analytics solution can send shivers down the backs of CFOs. They’re looking for answers to important business questions, but they struggle with the amount of time and resources, typical with inflexible legacy systems, needed to do analytics right. Often, support for analytics is centralized within the IT organization, where the team is already stretched thin with other pressing projects and may miss or not fully understand the context around the problems that need to be solved.
Progressive CFOs aren’t standing still. To get the insights that will help them drive their organizations forward—and to help their business partners make decisions better aligned with financial goals—they are changing the way they operate. They are building analytics teams within their own organizations in partnership with IT. These finance leaders are adopting self-service analytics tools that are cloud-native and adhere to corporate security and governance policies and procedures. Self-service analytics give business users—in finance and in other parts of the organization—easier access to insights from different types of data from more sources than they can today with even the most robust embedded analytics.
By deploying a cloud analytics solution, IT is enabling analytics teams to quickly spring into action. And, with self-service data prep capabilities on the near horizon, it will be easier for finance teams to blend and transform multiple data sets that may be housed in disparate systems.
The Potential Impact of Self-Service Analytics
Self-service analytics has the potential to transform every facet of an organization. It will enable the CFO to give human resources, marketing, product, sales, and operations access to the financial information they need to do their own data discovery and visual analysis, so that they can understand the bottom-line impact of their decisions.
With the right tools, business managers, business analysts, and employees who take the initiative on finding answers will be able to blend data sets together to answer questions with more context. For example, a financial analyst could move well beyond aggregate measures like average store profitability, and on to the fine-grained drivers of profitability by specific product lines within specific stores. This ability to easily hone in on small details can ensure that a finance organization’s strategy and discipline is shared by marketing, product, and other core operations.
Let’s look at some other things organizations could do with the right self-service analytics tools:
- A retailer or quick service restaurant could analyze profitability down to a store or even individual SKU by marrying point-of-sales systems with merchandising classification hierarchies.
- A business-to-business enterprise could improve financial forecasting by joining financial data with pipeline data to analyze not only current growth rates, but also to better understand how the opportunity backlog might impact future revenue.
- A hospitality company could bring in public sources of data such as hotel reviews, ratings, or weather information to present a holistic business dashboard, including financial, operational, and contextual metrics.
Certainly, data governance and security controls need to be in place when financial and human resources data become democratized across an organization. Processes must be established to ensure that third-party data is accurate, defined appropriately, and up-to-date. Analyses are most useful when tailored, such as providing store managers with dashboards populated only for their specific stores or regions.
The Future of Self-Service Analytics
As businesses continue to move core applications to the cloud, we think we’ll continue to see analytics teams increasingly moving into the finance function. And, in a virtuous circle, as business users realize the value of doing analysis at the speed of thought, the adoption rate of self-service analytics and data prep will skyrocket, and the ability to blend data from numerous sources will drive more business value than ever before. Ultimately, data-driven decisions will become an even bigger part of a company’s culture.
What I’ve described above is what we’ve set out to accomplish with Workday Prism Analytics, which layers self-service data prep and data discovery technologies from Platfora’s modern BI and analytics solutions into Workday’s technology platform.