Cloud Journey - Part 9 | Cloud for CFOs
Cloud Journey Series:
In this post:
Autonomous Finance
In an autonomous finance function, processes and activities are partly governed and majority operated by self-learning software agents that optimize front-, middle- and back-office operations. An autonomous finance function isn’t just automated; it’s capable of delivering augmented real-time and predictive insights, effortless compliance and greater flexibility in financial strategy.
Three CFO mindset shifts to achieve autonomous finance:
Building blocks of Autonomous Finance
Cloud
Investing in cloud is a key building block for autonomous finance given the ability for continuous innovation, automation and faster value realization. Cloud accelerates time to market with features and products that can scale and operate with less overhead. But despite the growth of cloud adoption in finance, it still significantly lags behind other functions. By 2025, cloud-native platforms will serve as the foundation for more than 95% of new digital initiatives — up from less than 40% in 2021.
Digital Talent
As autonomous finance initiatives ramp up, it’s imperative to recruit the right digital skills across the finance team and throughout the business. But leaders face unprecedented talent challenges with competition for attracting and retaining employees. Plus, expensive talent is scarce — 47% of CFOs report it’s difficult to find and hire enterprise talent. CFOs should partner with HR to define digital skills, bring them into the hiring process and rethink how to retain these skills. Among strategy, attraction, attrition and employee engagement, a digital talent strategy involves:
Data & Analytics
Finance teams often struggle to create valuable reports and analyses because of a misalignment between finance’s approach and the business’s needs. Piecemeal investments in finance data and analytics have contributed to fragmentation, where data, tools and expertise exist in silos across the organization. Common indicators of fragmentation include:
Within an autonomous finance function, finance delivers valuable insights to decision makers, finds innovative ways to use analytic resources and connects business problems to the data to help inform better decisions.
Artificial Intelligence
Leading AI finance organizations aren’t always the ones investing the most in AI, or the ones that have used AI the longest. Instead, they invest in specific ways or specific capabilities and more readily experiment with the following actions:
Example AI use cases in finance:
Blockchain
While blockchain implementation may not be a priority for CFOs , it is a critical component to the future of business and the finance function. Especially as CFOs face unprecedented economic headwinds, implementing blockchain is key to driving better, faster and smarter decision making to meet the demands the business faces now and in the future:?
CFO's Top Priorities for 2023
2. Develop and refine the data and analytics strategy.
3. Align spend to growth.
4. Improve finance staff engagement.
5. Set finance’s technology strategy and roadmap.
FinOps
FinOps brings together the ideas of engineering teams and financial departments to establish a transparent and defined process, when private or public clouds of different cloud providers in multiple locations are used optimally and consider cost, performance, capacity and company perspectives. It helps to build a process of constant optimization, improve cloud usage experience, control cloud resources and their expenses.
Organizations that use FinOps effectively can reduce cloud costs by as much as 20 to 30 percent (this is different than building things ineffectively then fix it and claim cost optimization).
To better understand where the FinOps pitfalls are in the cloud migration process, and how to avoid them, read this McKinsey article.
When investing thousands of dollars into cloud infrastructure, it is obligatory to be sure that you do so in a proper way. An interesting lesson emerged from 2020 to help one understand the importance of setting up FinOps practice and to avoid budget overruns in future. It was a free trial experiment3 which ended with a whopping $72,000 bill overnight. It sounds impossible, but this is the real case of an unpredicted GCP bill. In such circumstances, it’s fair to say that FinOps is a necessity nowadays.
You can read more about FinOps and techniques to improve the cost optimization in this booklet but a very quick basic 5 steps:
Step 1. List all the stopped instances in your account. Filter the ones that are stopped longer than some period (one or three months etc.), think if they are still needed and remove them otherwise.
Step 2. List all the unattached volumes and snapshots not used for any of the machines. Remove the unused.
Step 3. Clean up your S3 buckets. I’ve never seen an account without some thrash files and objects, duplicates, etc. If you need something, keep it in S3 or move into Glacier to save money.
Step 4. Identify unused IAM users and list their resources. There is a high probability of inheriting unnecessary cloud resources left when people quit. Think about whether you still need them.
Step 5. Check whether you have cross-region traffic and, if yes, think if you really need it. It’s one of the top cloud expenses, but people actually forget about it. If there is no reasonable cause to stay in different regions, consolidate resources under one region.
And TAG, TAG, TAG your resources. Have a proper naming policy. It’s common when every engineer names resources as he or she wants, and later it’s impossible to identify an owner.
Composable Finance Technology
The lack of an agile, modern and holistic decision-making framework for finance technology results in poor technology selection, delays in system delivery, increased costs, increased operational complexity and an environment that stifles innovation.?Even worse, failed technology projects can affect existing and future business operations, customers and supplier relations, potentially harming the overall market standing of the organization.
The composable finance technology strategy is?a modern and effective approach for?CFOs?to?assess?and plan their?technology?portfolio. It helps finance evolve its technology landscape into an ecosystem of modular, composable application building blocks that enable a more agile and business-centric finance organization.
Traditionally, most organizations’ finance technology planning can be summarized as:
Mistake?1: “Thinking and Selecting Large Systems” Reduces Business Agility
Large, multifunction systems, particularly enterprise resource planning (ERP) applications, are fundamental to finance’s work but underperform in multiple ways, particularly agility. Many organizations seek to use the ERP?application?alone to run their operational and financial processes but find that finance has fallen short on the ability to plan, design and execute responsively. For example, end of month batch processing within?ERP?still follows a linear process. It starts with freezing subledger transactions at month end, followed by multiple days of closing routines in the GL, financial statement preparation and reporting.?This linear approach can delay a business’s response to?an event that happened in the prior month by weeks.
Mistake?2: “A Single-Vendor Approach” Inhibits Innovation
CFOs traditionally have sought a single-vendor approach for all their functional needs (transactional finance, closing, reporting, planning) to avoid integration problems and to create a “single source of truth” for the organization. However, a single-vendor approach leads CFOs to?overly?on vendors to drive innovation within their function. If a vendor’s product strategy and roadmap does not prioritize innovative finance capabilities (such as user experience, mobile platform, blockchain, AI/ML), CFOs?risk missing important opportunities?for innovation.
Mistake?3: “Standardizing All Finance Processes” Erodes Competitive Advantage
When finance embarks on any technology implementation, leaders often seek to standardize all processes and then implement the technology on top of the standardized processes. Though this approach may work when the process’s goal is to reduce inefficiency or drive compliance, a large and growing share of finance capabilities are?not?efficiency-focused. This is particularly true in areas such as reporting and analytical processes whose objectives are insight generation and supporting decision making. Applying standardized,?efficiency-focused?thinking stifles innovation and erodes competitive advantage where finance can drive value by being unique or enabling capabilities specific to their industry or customers.
For?example, consider an organization for whom cash collection in the invoice-to-cash process is particularly critical. If they follow the traditional approach of standardizing the collections strategies based on customer accounts receivable (AR) aging or past dues, they risk losing any innovation they could have enabled in their process by including external drivers (such as credit ratings) or internal drivers (such as payment behavior trends) to predict customer risk of no or late?payment. Here standardization may simplify processes; however, it?erodes the competitive advantage finance could have gained by driving faster cash flow for their organization.
Mistake?4: “Design to Last” Mindset Stifles a Culture of Experimentation
With any technology implementation, finance leaders often spend many months designing the “perfect” system, thinking that if they do it right, they only have to do it once, and their system design will last them for many years. Consider a traditional ERP implementation. Business, finance and IT stakeholders often spend months (sometimes years) working to define the end-state design only to find that?the business, and its associated requirements, have changed since the initial planning phase.
The “once and done” implementation approach to any technology?deployment?no longer works; businesses and technologies are simply changing too quickly. The days of hanging on to ERP instances or FP&A planning tools for 15 years or more is over. The transition to cloud-based technologies has dramatically shortened product release cycles, making new features available much more quickly than in the on-premises environment. The traditional “design to last” mindset leads technology architecture to become inflexible to experimentation,?which often drives new business requirements being managed “offline,” outside the “official” technology ecosystem, governance models and support structure.
Where the?traditional?finance?technology?paradigm is designed around large complex systems, familiar vendors, and standard and inflexible design, a?composable?paradigm is designed around modular?technology solutions and best-fit vendors that?deliver?specific finance capabilities. Composable thinking enables finance to balance between stable applications for standard capabilities and innovative applications in areas where the organization requires more agility or differentiation. The change enabled by technology is embraced as an essential tool to support growth and build organizational resilience.
The composable finance technology architecture?framework organizes?finance technology architecture into modular application building blocks that deliver well-defined finance capabilities in support of?specified?business outcomes. These application building blocks may either be purchased or?developed?in-house and are organized within composable platforms?connected by APIs?to the broader enterprise technology architecture.
A?composable platform?is a?group of composable applications that have related finance capabilities. For example, the AR composable platform comprises a group of composable applications each representing a unique?finance capability?such as?AR analytics, managing collections, managing customer payments and managing cash applications.
To guide the design of their composable platform, finance should:
Composable platforms are assembled to create unique experiences, tailored to individual finance preferences such as for an FP&A planner or accounting close leader. Hence, the granularity of each composable platform should be determined based on how each finance role consumes these capabilities.For example , in the close process, controllers typically consume most close capabilities (such as consolidation, reporting, reconciliation) together to complete their end-to-end workflows. Whereas in certain industries (such as the healthcare industry), customer billing may be managed by different finance users or functions and hence customer billing platforms and AR platforms will be distinct composable platforms.
To enable platforms to evolve rapidly without disrupting other platforms, composable platforms should be self-contained. For example, though data flow occurs across period closing as well as planning and budgeting platforms, each platform should be sufficiently autonomous to allow finance to independently enable new capabilities such as scenario modeling in planning or anomaly detection in closing without disrupting other platforms.
The composable finance technology architecture is divided into three categories or layers. Each composable platform falls within one layer based on the main purpose and value it delivers:
Because a composable finance architecture is organized around enabling finance capabilities, it is helpful to consider an example of the record-to-report (R2R) process. This process is one of the most fundamental and most technologically complex finance processes, typically involving the orchestration of multiple different composable platforms. While many organizations focus on standardizing and driving compliance within the close process itself, many are also working to significantly increase the value of reporting activities during the close by investing in differentiated and innovative capabilities.?Figure?8?provides an example of how an organization may structure the R2R capabilities and their associated composable platforms within the three layers of the composable technology architecture.
By using a composable architecture, a flexible governance structure that tailors to the needs of composable platforms in each layer is possible.
As shown in above figure,?the technology governance process changes as you move from core to innovative platforms in key areas: