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Delivering a Better Forecast: Five Keys to the Successful Adoption of Advanced Technologies In Finance

James W. DeLoach

Managing Director

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In his science fiction novel Pattern Recognition, author William Gibson wrote, “We have no future because our present is too volatile. We have only risk management. The spinning of the given moment’s scenarios.” Gibson’s works have been credited with foretelling cyberspace and the Internet Age. His digital storytelling also is a parable for corporate finance’s 21st-century transformation. A growing number of CFOs and finance leaders are deploying a blend of advanced technologies to help reduce risks, cut costs and mine data for compelling finance- and risk management-related insights and narratives.

While these technologies can deliver numerous advantages and capabilities, the CFOs and finance groups leading the way in adopting advanced tools succeed as much due to their perspectives and processes as to the automation itself. Digitally advanced CFOs know where and how to allot their transformation time, energy and investments.

Financial planning and analysis (FP&A) groups are especially ripe for emerging technologies, including but not limited to artificial intelligence (AI), that can help them shift their gaze from historical performance metrics to massive data sets that yield forward-looking insights to strengthen forecasts, anticipated scenarios, projections and plans concerning products, supply chains, logistics capital allocation, and financial and operating performance.

Although leading CFOs embrace their role as stewards of data and advanced technologies, that doesn’t mean they are, or need to become, full-fledged data scientists. They remain as focused as ever on driving cost savings, risk reduction and predictable outcomes. These CFOs optimize their growing need to invest in advanced tools by having the right people in place and pulling the right process levers, especially as they oversee the following five areas to help their finance organizations achieve their transformation and technology objectives:

  1. Develop a holistic technology and automation strategy: As finance teams create and update roadmaps for investments in robotic process automation (RPA), business intelligence tools, AI applications and other types of advanced automation, they should avoid looking at these tools discretely. For example, rather than assessing RPA in a silo, consider how RPA can be combined with machine learning to deliver additional benefits. The initial substantial investment in AI or another emerging technology may feel like a leap, but it should be treated as part of an ongoing evolution during which the combination of tools that are best suited to the finance organization becomes known. Keep in mind that with regard to the different advanced technologies available, they often begin with or in the cloud. Cloud technology serves as a foundational enabler for most investments in advanced finance tools. Cloud environments facilitate data access and, in many cases, the centralization of emerging finance technologies such as RPA, AI and other forms of machine learning. Without sufficient cloud capabilities in place, organizations can get bogged down by efforts to extract data from a tangle of on-premises legacy systems and applications.
  2. Embrace centralization (and strive for excellence): The finance groups that gain the greatest value from advanced technologies tend to house them—the tools themselves as well as the data that fuels them—in a shared services or center of excellence model. Centralizing the data that feeds different advanced tools eases the management and oversight of that data and accelerates the deployment of new tools. This type of centralized platform also facilitates related training, sharing of practices and innovation activities.
  3. Find change champions: In a previous article, I noted that rapidly expanding data sets can cause discomfort in the control-and-accuracy side of the traditional corporate finance brain. Having the finance organization use advanced technologies and tools can create similar uneasiness. That’s why CFOs should focus on identifying change agents on their teams or in the organization’s ranks who are willing to depart from the status quo, eager to explore new technologies, and open-minded about the fact that automation-related changes will come with challenges despite the benefits they deliver. Finance transformation champions also can reside on the board and in the CEO’s office.
  4. When aligning with stakeholders, include HR: Finance teams that have advanced furthest on their digital journeys devote sufficient care and effort to three critical enablers: stakeholder alignment, communications and training. Stakeholder alignment is especially important because it can strengthen the communications and training that the digital and technology change effort requires. Stakeholders likely are both inside the organization (e.g., information technology and human resources colleagues) and outside of it (e.g., vendors and business partners). Finance-IT alignment on advanced technology development and investments often receives sufficient attention because IT possesses direct subject-matter expertise. However, HR’s involvement in the adoption and use of advanced finance technologies is just as important. HR can help finance propel its change management agenda by supporting talent acquisition as well as employee skilling and communications (e.g., helping to set, and recalibrate as needed, the content and frequency of finance transformation communications).
  5. Take ownership of technology training: Prior to the advent of cloud technologies, organizations tended to rely on third-party technology providers to deliver the lion’s share of training on new systems and applications. For example, when a finance organization implemented an enterprise resource planning (ERP) system, acquired a new FP&A application or replaced its procure-to-pay system, it generally depended on the technology vendor or systems implementer to train users of those systems. In the emerging technology realm, though, fit-for-purpose solutions outnumber out-of-the-box finance solutions. This makes standard training programs less viable. As a result, we see more finance teams collaborating with their IT and HR colleagues to develop customized training, often as offerings within the finance organization’s advanced automation center of excellence.

In summary, embracing the emerging technologies that drive finance and digital transformation does not require CFOs to become technology experts or data scientists. It does require them to possess and convey a clear holistic view of the finance organization’s technology and automation strategy. It also requires them to update the finance organization’s ability, through advanced technologies and other means, to generate more forward-looking insights from a much larger collection of data. Those insights will produce not only more accurate cost assessments and better forecasts but also more meaningful underlying CFO narratives that resonate with internal partners and external customers alike as well as in the C-suite and boardroom.

This article originally appeared on Forbes CFO Network.

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James W. DeLoach

By James W. DeLoach

Verified Expert at Protiviti

Jim DeLoach has more than 35 years of experience and assists companies with responding to government mandates,...

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