CFOs can be slow to adopt new technologies out of fear. But you can help them understand the benefits of implementation.
After a year of enduring COVID-19 and halting progress on key technology projects, CFOs appear to be ready to renew investments into projects that further the implementation of advanced analytics and automation technologies such as robotic process automation (RPA), according to a recent Gartner survey.
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There are two reasons for this.
- Especially in finance, where analytics around key financial ratios and metrics is paramount, there is a call for more sophisticated analytics that can improve performance.
- RPA is principally a keyboard automation technology that eliminates rekeying of the same data into multiple systems that can't be integrated. Repetitive keying is a problem in finance, where a plurality of the systems don't integrate well with each other.
At the same time that analytics and RPA are being listed as high priorities, there is also a hesitation of CFOs to open wallets for these technologies. In the same Gartner survey, 78% of CFOs expressed doubt that they could easily reach their goals in advanced analytics, and 56% were concerned that they couldn't achieve goals in implementing RPA.
This should concern IT.
First, finance is a bellwether for how executives in other company departments feel. In other words, the same set of priorities, accompanied by similar levels of trepidation, might also be present in other departments. Second, it's CFOs who wield the power to nix or approve most IT projects in analytics, digitalization, and big data—no matter where and for whom these projects are undertaken.
What steps can IT leaders take to ensure that CFOs are on board with analytics and other digital transformation projects?
1. Guarantee project success
Design projects that have achievable goals and tangible returns on investment. Shorter projects that demonstrate success build confidence so longer-term, more high risk projects can happen.
2. Know your users' weaknesses
In the case of finance, the department wants more analytics, but can quickly get entangled into them and lose some of the big picture.
For example, you can look at financial ratios and results, but still lack understanding of operational elements that affect the bottom line. Customer service might employ analytics to see which customers are satisfied and which are not. This is helpful in anticipating customer attrition and in predicting which customers are most likely to develop long-lasting loyalty. Likewise, manufacturing can use analytics to predict equipment failures before they occur. This keeps production moving and averts expensive downtime.
Both are examples of analytics that contribute to corporate financial health, but that finance might not be aware of. If IT also shares these analytics with finance, CFOs would likely find them to be value-added. This could make it easier for IT to promote non-finance analytics projects to the CFO and other skeptics.
3. Explain that RPA isn't the only way to eliminate repetitive work
While RPA isn't the only way to automate and eliminate repetitive work, it's the most immediately impactful way for finance to see the benefits of automation on its own workload.
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Automation and elimination of repetitive work can be achieved in areas like facilities, engineering, manufacturing, purchasing and customer service, by using automation technologies that differ from RPA. This is an area where IT and end users from other company areas should present clearcut business cases, with the technologies explained in plain English, and the ROI being expressed in hard figures.
Why it's important
The end goal is to get the CFO engaged in how big data, analytics, Internet of Things (IoT), and automaton can work throughout the company to deliver better revenue and operational results, regardless of the type of technology that is used.
There will always be a modicum of risk and uncertainty with any IT project, but having the CFO and operational business units fully invested in project success is a major step toward successful implementations.
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