The CFOs Guide to Better Analytics


Finance Insights for ProfessionalsThe latest thought leadership for Finance pros

Friday, October 9, 2020

Since the Covid-19 pandemic took a stranglehold on world affairs, the acceleration of digital capabilities has taken on new levels of importance. Despite ongoing digital transitions, many organizations found it tough to react to changing customer demands and working conditions. This has demonstrated more starkly than ever before the need for agile, data-driven modes of working.

Article 5 Minutes
The CFOs Guide to Better Analytics

In recent years, business leaders have been increasingly embracing the potential of data analytics, looking to harness a piece of the massive economic value it’s predicted to add. Data-driven business models are clearly nothing new, as anyone who’s grown tired of the term ‘digital transformation’ will attest. While the phrase has perhaps been overused, the concept itself is more integral to successful business.

Data analytics is already widely recognized for its ability to identify and solve problems, sometimes before they occur. In a post-Covid market, this will become an essential navigational tool if businesses are to survive or thrive.

For CFOs, data analytics, machine-learning and other artificial intelligence tools offer an unprecedented chance to drive value for your organization, but you need to get it right. The secret could lie in analytic process automation (APA).

What is Analytic Process Automation?

To some extent, APA does what you think: it uses technology to automate data analytics. But it differs from better-known automation tools in a few key aspects, and they could be the difference you need to take your organization’s analytics to the next level.

While many of the tools in use today require expert knowledge and can, in some cases, take months to fully implement, APA removes the barriers to analytics by converging multiple tools into one platform. It’s an end-to-end solution that fully accelerates the production of insights a CFO needs to take actions that drive value across the business.

APA works by solving the dilemma of simultaneously leveraging data, business processes and people in a unified platform that offers automated capabilities for all analytics functions (diagnostic, predictive, prescriptive, and geospatial analytics). A crucial aspect of APA is that it delivers code-free data science, which makes it accessible to anyone in your organization. This sets it apart from niche analytics tools and could kickstart a truly digital transformation across your organization.

Today, CFOs are expected to be able to provide in-depth data insights that drive decision-making and business strategy beyond the finance department. APA is a tool that can enable that drive by empowering any employee to leverage data insights.

Why CFOs should take the lead on data analytics (and how to do it)

There are a handful of ways you, as a CFO, can take the lead on analytics within your business. With the help of APA, you can define the business areas in which analytics will deliver the best economic value, thus demonstrating why finance should be at the forefront of your organization’s data capabilities.

Gain a competitive advantage

Finance has long been data driven. Now, the proliferation of big data and the tools to analyze it mean it’s more important than ever to employ data to steal a competitive advantage. By taking the lead on data analytics, CFOs can expand their traditional strategic role to cover operational decision-making as well.  Analytics can help to consolidate a more centralized approach to business decision-making, providing answers to questions such as:

  • What inventory needs pulling forward/out
  • What price should be presented to this customer today.

Greater stability in volatile markets

With excellent analytics, CFOs can take the lead in both business strategy and operations. Investing in advanced data analysis can help to guard against (or at least prepare for) volatility and build the agility needed to respond faster to changes in the marketplace. As we’ve seen in recent months, organizations that already had these capabilities have been able to withstand the economic wrecking ball of COVID-19, flourishing under the most difficult circumstances imaginable.

Data-driven decision making

CFOs are traditionally involved with big-picture strategy, rather than day-to-day operations, but analytics provides rich insight into the customer and the marketplace. Being able to act effectively on that knowledge is what will boost your bottom line. Data-driven decision making can instill operational discipline and stop profit being leaked through the gaps in your business operation.

Streamline business profitability

By identifying analytics capabilities that cut across departments, CFOs can deliver business-wide profitability at an operations level. One of the simplest ways to do this is to illustrate the extra value that data analysis can bring to inventory management. Alternatively, you could identify areas where marketing spend could be better allocated. The key is to locate a central business need and demonstrate how data-driven financial decisions can fulfil that.

Enable business growth

In uncertain times, when tides continue to shift on an almost daily basis and entire industries await the fallout of the global pandemic, the predictive and resilience-building prowess of data analytics can enable your organization to continue its growth despite those challenges.

‘Analytics supports numerous urgent tasks facing businesses today: forecasting demand, identifying potential supply-chain disruptions, targeting support services to at-risk workers, and determining the effectiveness of crisis intervention strategies, to name a few’ McKinsey, 2020.

There’s an opportunity here for CFOs to grasp the baton when it comes to analytics. It’s always been important to financial decisions, but now financial leaders can extend their purview across an organization, enabling them to deliver value across all departments and break the silos that have typically stunted growth in certain areas, simultaneously strengthening their own position.

Traditionally, the establishment of a data-driven culture has been a hefty organizational challenge. It requires the disassembly of legacy systems and a changing of mindsets. By utilizing analytic process automation, you can take some of the difficulty out of your data transformation and set your organization on the way to a more agile, successful future.

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