Cloud Journey — Part 9 | Cloud for CFOs

Chris Shayan

15 min readApr 28, 2023

Cloud Journey Series:

Cloud Journey - Part 1. A basic introduction of cloud, applying PACE layering and The 6R's.
Cloud Journey - Part 2. A quick review on what is the good organization chart to enable cloud journey.
Cloud Journey - Part 3. A quick view on Business Values and Business Drivers on a cloud journey.
Cloud Journey - Part 4. What does cloud mean for your "Talents & Culture"?
Cloud Journey - Part 5. Using Platform Ops to accelerate DevSecOps adoption
Cloud Journey - Part 6 | Foundations of Cloud Architecture
Cloud Journey - Part 7 | Customer Data Platform (CDP)
Cloud Journey - Part 8 | Customer Data Strategy
Cloud Journey - Part 9 | Cloud for CFOs

In this post:

Autonomous Finance
CFO’s 2023 Top Priorities
FinOps and Strategies
Composable Finance Technology

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:

Experiment to realize value from technologies.
Give autonomous finance as much credit as people.
Advocate for autonomous finance technologies.

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:

Developing critical digital skills. As data becomes more real-time and available to the business, it’s critical to have decision makers that have the appropriate business financial IQ to leverage it in a meaningful way.
Redefining the employee value proposition (EVP). Rethink how to create a culture and sustainable environment for staff as the finance function becomes more autonomous. Think through the new work environment and use finance technology roadmaps to engage staff in helping to define and build a future state of the organization.

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:

Acquire new AI-specific talent.
Purchase technology with embedded AI capabilities.
Experiment broadly with the use of AI.
Choose an analytically savvy leader to realize the benefits of AI.

Example AI use cases in finance:

AI-enabled process mining algorithms capturing all variations and exceptions in procure-to-pay (P2P) and order-to-cash (O2C) in back office
Machine learning identifying and organizing data from various sources in a single place and enhancing the accuracy of information

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:

Information management. One of the core components of blockchain is a disrupted ledger, which allows for a more accurate and efficient flow of information inside and outside of the organization — and in a way that’s more easily verified. This creates better insights for the business and more sound decision making all in the foundation of trust.
Reporting. A single source of truth is critical for operations across the enterprise. Blockchain provides that single source or “golden copy.” Visible transactions help with efficiency and collaboration, which prevent obstacles.
Agility. We live in a dynamic world. Blockchain allows you to improve the agility of your organization because it breaks down silos and creates a network-based system that operates as a fluid ecosystem. A top priority for finance leaders is to reallocate capital based on changing business needs. Blockchain provides real-time data to do just that: alter business cases, monitor investments, track transparency and stop/reallocate funds mid-cycle to drive the right digital enterprise strategies.

CFO’s Top Priorities for 2023

Lead finance transformation and organizational change initiatives.

Action 1: CFOs cannot fully delegate transformation initiatives; instead, they must define objectives and commit to being personally involved in transformation.
Action 2: CFOs must ensure that finance transformation leaders have three key traits to achieve success: acute vision, relentless triage and purposeful communication.
Action 3: Successfully engage your staff in your transformation initiatives by: introducing fewer, more sustainable efforts; providing targeted, need-based change support and coaching; and including employee perspectives in the decision-making process.

2. Develop and refine the data and analytics strategy.

Action 1: Align FP&A scope and design with organizational strategies and priorities.
Action 2: Use the Gartner Risk Opportunity Appetite Return (ROAR) model to drive business value from data and analytics (D&A) investments.

Action 3: Embed D&A into business strategy and digital transformation by creating a vision of a data-driven enterprise.

3. Align spend to growth.

Action 1: To enable capital responsiveness, CFOs and their teams must move from the role of a “reviewer” to a “capital activist.”
Action 2: Instead of perpetually spending to keep up with competitors, CFOs need to reorient their cost structures to focus on differentiating costs.
Action 3: Instead of just incentivizing business managers to take more risks, counter the unintended side effects of finance processes and policies that redirect resources away from bold growth projects.

4. Improve finance staff engagement.

Action 1: CFOs must update and leverage the organization’s unique employee value proposition to engage employees.
Action 2: CFOs should effectively communicate strategy to employees to form personal connections between the organization’s strategy and the employee’s work.
Action 3: CFOs can increase retention of digital talent by creating a sense of belonging.

5. Set finance’s technology strategy and roadmap.

Action 1: CFOs need to embrace composable finance technology to increase finance responsiveness to changing business realities.
Action 2: Leverage the Gartner Technology Bullseye to prioritize technology investments with the highest impact.
Action 3: Build a cohesive, forward-thinking technology strategy by incorporating the latest technology trends, such as distributed enterprise, generative AI, data fabric, autonomic systems and cybersecurity mesh

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:

Think and select large or complex systems that support multiple business and finance capabilities.
Rely on a single-vendor approach for all finance technology needs.
Focus all technology implementation on standardizing finance processes.
Follow a design-to-last mindset when implementing finance technologies.

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.

Base composable platform granularity on how capabilities are consumed.
Ensure composable platforms are sufficiently autonomous and have minimal dependencies.

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:

Core Platforms — Enable standardization of common finance capabilities.
Differentiated Platforms — Enable differentiation of value-added capabilities.
Innovative Platforms — Enable innovation of new capabilities.

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:

Finance engagement — Within core platforms, we see more formal and limited engagement of finance (as a stakeholder in the steering committee or a subject matter expert in design validation and system testing). As you move to innovative platforms, finance takes a stronger leadership role in vendor selection and ongoing vendor relations. Finance now becomes a key participant in system implementation and in some technologies (such as predictive analytics); they may contribute to the development work.
Funding Model — Core platforms tend to be long-term capital projects following a standard capital approval process. Innovative platforms are experimental, and the costs and benefits may be unclear at project inception. Here, organizations may choose to allocate money for these types of projects in the budget and then disperse funds based on requests during the year. This can be attributed to a venture capitalist model, where later rounds of funding will be awarded based on what is accomplished, eliminating projects that don’t pan out.
Measure of success (ROI) — Investments in core platforms should be determined based on whether the incremental funding will reduce complexity of finance operations or improve compliance. This will enable CFOs to pause funding in core platform projects when they reach the “good enough” stage. Differentiated platforms should be measured on the business value (increase revenue, cash, margins, etc.) they provide to the organization. Innovative platforms are expected to challenge the status quo and encourage experimentation, and hence they are expected to have higher failure rates. These platforms should be measured on the new finance capabilities and business models they are able to support.
Technology development practices — Core platforms tend to follow the classic waterfall application development where requirements, design and testing follow a sequential pattern. This will give way to a more agile and rapid software development methodology within innovative platforms.
Change control process — Core platforms require strict change control to ensure any platform change or update doesn’t drive unintended consequences and ensures regulatory compliance. Innovative platforms are experimental and will change frequently, which requires an expedited approval process.
Planning horizon — The planning horizon relating to investments and funding will reduce more rapidly as organizations move from core platforms to innovative platforms.