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Challenge of Finance Best Practices and What CFOs Should Do About It

The modern CFO is touted as the right hand man of the CEO, providing strategic and operational decision support. No longer is the CFO only responsible for preparing and interpreting financial statements based on historical accounting data, but also for taking a holistic view of business performance and helping the organization move forward.

Thanks to new technologies and improved business operating models, CFOs across industries have been able to transform finance into a value creation function. Further, finance leaders are overwhelmed with finance best practices advice from professional services firms, research analysts and consultants.

Finance leaders are advised to standardize ERP systems, adopt financial planning and analysis technologies and ditch spreadsheets, streamline budgeting processes and implement driver-based rolling forecasts, automate and accelerate financial close and reporting etc.

The list is endless, but does a complete reliance on best practices advice improve finance’s performance and value creation?

Best practices and benchmarks are meant to help business leaders assess the progress of their companies against “leading performers” as opposed to being aspirational ideals to be attained.

The challenge with viewing best practices as standards of excellence is that, their attainment might mistakenly be interpreted by business leaders that no further effort, experimentation or thought is required.

By their nature and application, best practices are transitory. Given today’s business world which is constantly changing – practices, processes, systems and operating models that have enabled us to drive business performance are no guarantee of future success.

CFOs therefore have to realign their functions if they are to keep pace with the demands of an increasingly dynamic marketplace. Always keep in mind that best practices are only beneficial as long as the circumstances in which they are established remain stable.

Unfortunately, volatility and uncertainty are the norm today.

As a finance leader, you should be weary of copying best practices from other businesses with little adaptation otherwise you risk stagnating creativity and commoditizing innovation across the organization.

Rather than continue to depend on the widely accepted best practices, CFOs need to adopt a new mindset, break old habits and promote a continuous improvement culture.

Many at items promising ideas never experience the light of the day because the culture management has created rewards success and punishes failure. Leave some slack for experimentation and encourge constructive failure.

Simply following a complete set of rules or principles will not, on its own, drive finance function effectiveness. Before jumping at the so called best practices, at least ask yourselves:

  • How are we doing what we are doing now?
  • Why are we doing what we are doing this way?
  • What would it look like if we didn’t do things this way?
  • Who expressed this is the best practice?
  • Why is it considered best practice?
  • Does the best practice work for our business?
  • Is the best practice still valid or outdated?
  • Under what circumstances was the best practice established?

Answering the above questions will help you validate the best practice and its potential to boost organizational performance.

Adopt ideas, processes, technologies, and skills that drive change and create value. There is no hard-and-fast playbook. In a culture of innovation, new ideas spring forth from all directions, especially from the unexpected sources.

Just because the organization’s existing structures, systems, skills and processes are driving performance today does not mean they will continue to do so in the future. The past is prologue but not necessarily precedent.

Finance leaders who continue to find comfort in implementing widely accepted best practices to secure competitive advantage or embrace “this is how we have always done it” approach in today’s increasingly uncertain world are not only squandering resources but also destroying value.

Finance as the Custodian of Enterprise Performance Management

The days of having CFOs responsible for only preparing the statutory financial reports of the business and play the role of the bookkeeper are long gone. Today, finance leaders are expected to play the role of the strategic advisor to senior management and the board,and help drive operational and strategic performance across the enterprise.

That is, become custodians of enterprise performance management (EPM) by taking the lead on performance management and delivering informed business insights. EPM takes a completely different approach towards measuring, monitoring and improving enterprise performance.

Instead of assessing business performance in a siloed approach, EPM ensures the business evaluates and monitors its performance holistically. Although a majority of business decisions have either positive or negative financial implications on the health of the organization, evaluating, monitoring and improving business performance extends beyond a sole focus on financial metrics.

In order to perform better in their new business performance custodian role, it is imperative that finance leaders develop knowledge and a deeper understanding what constitutes and doesn’t constitute EPM. 

A simple google search of the words “Performance Management” brings up results that associate performance management to the process of conducting employee performance appraisals and supervising employees and departments to ensure that goals and objectives are met efficiently.

As a result, many people think that performance management is a human resources process that is only people-focused and has nothing to do with finance – Human Performance Management. To a lesser extent, their thinking is correct in the sense that people are part of the process. However, to a larger extent, they are wrong.

Performance management is not entirely focused on carrying out the outdated employee annual performance appraisals or reviews based on isolated individual key performance indicators (KPIs).

Rather, performance management is the integration of multiple managerial methods and or frameworks such as strategy maps, balanced scorecards, activity based costing/management, driver-based rolling forecasts, process improvement, risk management and advanced analytics to support strategic decisions and drive performance.

This is not achievable individually, hence the key word “enterprise.”

As custodians of business performance, finance should play a leading role in implementing a robust EPM framework across the organization. The framework should enable the organization to communicate and translate its strategy into financial and non-financial metrics and targets, monitor its performance, create accountability, and focus its efforts and resources on the key business drivers.

Additionally, the EPM framework should ensure there is alignment between individual KPIs and reward and recognition systems, and corporate objectives, as opposed to mere job descriptions, in order to encourage behaviours which positively contribute to the overall strategy of the business.

When implementing the EPM framework, it is important to ask the following questions:

  1. What do we want to achieve and excel at? This helps define your goals and key value drivers.
  2. How do we know if we are actually excelling at this? This involves defining financial and non-financial KPIs, which are measures that help you understand whether you are achieving your goals
  3. What is the desired level of performance that we would like to see? Defining KPIs is not enough, you also need to define your targets that represent the level of success or failure at achieving your KPIs.
  4. What initiatives should we pursue or engage in to meet our performance targets? These are actions or projects or strategies or processes needed to achieve a target, or improve performance level.
  5. What resources and or investments are needed to achieve our target? Utilizing driver-based budgets and dynamic rolling forecasts will ensure resources are allocated strategically and efficiently.

Asking and answering the above questions helps design and implement management processes and systems that align business strategy to drive accountabilities, decision support and performance improvement.

For example, when KPIs are aligned with business strategy, decision makers will focus on the critical success factors of the organization. On the contrary, if there is lack of KPI alignment, senior management end up getting overwhelmed with an increasing number of performance reports that lack key insights necessary to move the business forward.

As custodians of enterprise performance, it’s important for finance to have the ability and capabilities to consolidate, analyze and interpret business performance in real-time. Rather than simply report on the past, finance teams must be able to explain the reasons behind the numbers (the whys and what-ifs).

Leveraging consolidation solutions enable teams to quickly model and assess the impact of alternative business scenarios and formulate appropriate solutions.  

Given the complexity of today’s business environment, finance leaders need to rise to the occasion and perform the strategic advisory role now expected of them by senior management and the board.

 

Finance Needs To Do More Than Prepare Reports

There is an ongoing discussion about the evolving role of finance and the function’s contribution towards enterprise performance improvement. Thanks to new operating models and emerging technologies, finance has been presented with an opportunity to step up and shine.

That is, focus more effort on providing effective decision support that drives organizational success and less on rote tasks that can easily be automated, outsourced or performed separately in a shared services center.

Providing effective decision support requires a deep understanding of the business in its completeness, the cause-and-effect relationships between business units, big growth drivers and performance drivers. It’s more than producing a complete set of financials on a monthly basis.

By virtue of their training, many finance professionals possess strong technical accounting backgrounds and limited business experience. For instance, preparing external reporting financials that are IFRS-aligned comes natural to them. At any point in time, they are able to interpret a particular standard, paragraph by paragraph, without even making reference to the standard handbook itself.

There is nothing wrong with becoming an accounting standard expert. The problem arises when the entire finance team is made up of financial reporting experts who spend the majority of their time churning out reports just to meet regulatory and compliance requirements and less on driving business performance.

Month-end, quarter-end and year-end reporting are still an important part of running a successful finance organization. It’s important that the financial statements are free from material misstatements and faithfully represent the financial performance and position of the business.

However, the process should not end there. Finance should also be able to interpret the reported numbers, create meaning and simplicity from them as well as communicate a point of view about how the numbers will inform strategic decisions.

It’s therefore imperative for finance leaders to continuously assess the tasks their teams are focused on. Begin with why. For instance, why does your team produce the reports it produces on a weekly, monthly and quarterly basis? What purpose do they serve in informing business decisions?

After you have answered the why question, you should be able to determine whether the activity, report or process is a value add or not.

Any activity, report or process that is not value enhancing should be discontinued completely or streamlined. This will in turn help you free up more time and channel resources towards issues and or initiatives that really matter to business partners and senior decision makers.

Given that individuals are creatures of habit, it can be difficult to let go of traditional practices or old habits.

Unfortunately, sticking with the familiar in a constantly changing environment will not do you any justice. Just because this is how you have always done things in the past and are used to does not mean you should continue on the same path of the tried-and-tested.

In addition to getting rid of old habits that are no longer able to withstand the test of time, it’s also important to ask if the company’s business model is still fit for purpose to address today’s demands and challenges, and more important, is it fit for purpose for the future? With the world changing so fast around us, a business never reaches a point where it has the ideal model.

The operating model needs to continue to evolve. Finance can help shape this model through spending time with business partners and engaging in a two-way conversation about the business and offering its perspective. Communication between finance and the business should not be limited to month-end reports only.

Leveraging our financial expertise, we can help drive change by helping the company identify sources of growth and operational improvements, allocate resources effectively and efficiently, and accelerate its performance over time.

Finance is often regarded as the purse-holder of the company, holding the power to greenlight some initiatives and redlight others.

However, in order to drive innovation and change, finance must learn to see the world not only through a finance lens but also through a business lens. Many finance professionals are conservative and risk averse in their approach. Taking risk is something perceived extraordinary. We need to transition from this kind of thinking.

There is of course balance between taking risk and mitigating risk, but if finance is inclined to opt for the later, value creation opportunities can be missed. It’s therefore critical that we do not succumb to analysis paralysis because it’s easier to lose the big picture of what is needed to drive the company’s success in a myriad of daily transactions or useless data.

In conclusion, if finance is to influence strategic decisions and add value, finance leaders should start asking if their teams are focusing on what really matters to the business or the function.

Third-Party Risk: What You Don’t Know Can Hurt Your Business

Thanks to globalization and advanced technologies, the world economy is increasingly interconnected and a borderless market. Businesses are no longer depending on their own resources and self-developed capabilities in order to achieve operational excellence, fuel growth and drive strategic success.

For example, a retailer headquartered in Toronto, Canada, doesn’t necessarily need to rely on local suppliers to meet its customers demand. A financial services company in London, England can now employ the services of a cyber security expert domiciled in Singapore. Today, businesses are no longer going it alone.

When entering into new lines of business or expanding into new markets, it is common for organizations to leverage third-party knowledge, skills or resources, and form partnerships, alliances, and other business relationships.  These external parties have suppliers, partnerships and alliances of their own too.

Given the interconnection between third-party relationships and the inherent risks, the ability to manage these relationships is critical to success.

Ignorance is no defense

The actions of third-party intermediaries have dire consequences on the business, not just financially but also legally, operationally and reputationally. Moreover, regulators are increasingly policing third-party relationships, and when something goes wrong, the penalties can be hefty.

Think of the U.S Foreign Corruption Practices Act, UK Bribery Act, EU General Data Protection Regulation, or Brazil’s Clean Companies Act. Even if a security breach or risk incident occurs on the other side of the world, entities or individuals found on the wrong side of the law will not escape unpunished.

Activities can be outsourced, but responsibility cant’t. It is therefore imperative that business leaders develop a deeper understanding of third-party relationships including the full spectrum of risks linking in each part of the organization.

You need to adequately examine your clients, vendors, consultants, agents and other business partners, know who they are and how they operate. A basic internet search or third-party website visit doesn’t cut it. A detailed integrity due diligence is required. You need to know your business partners’ qualifications, business history, reputation and their relationship with foreign government officials.

In addition, you also need to understand the business rationale behind including the business partner in the transaction. Failure to do so could expose your organization to reputational damage, operational risk, government inquiry, monetary penalties and even criminal liability. What you don’t know about your business partners can hurt you.

Visibility over third-party business relationships

In a number of organizations, the examination of business relationships and assessment of inherent risks is left in the hands of the procurement function. The function identifies potential savings from outsourcing, the legal team drafts the contract and it’s business as usual. There is no or little follow up on the relationships.

In some cases, external relationships are managed in silos within business units. The business unit that owns the relationship also manages the risk. These individual business units have different ways of tracking their suppliers, vendors or partners, making it difficult to compare and collate them across the entire business. In addition, sometimes there is a duplication of efforts and inconsistent application of risk assessment and management standards.

In other cases, companies adopt a centralized or hybrid approach in order to help overcome the challenges presented by the decentralization model. With the centralized approach, redundancies are reduced, and risk decisions reside with a single group in turn fostering accountability for risk assessment.

However, it is important to note that with this approach tensions can sometimes arise between business units that have a working relationship with the external parties and the centralized team accountable for risk assessments. As a result, some companies pursue a hybrid model in which risk ownership is clearly defined and decision making rights are spread across a number of business functions, such as procurement, finance, compliance and risk management.

As the business is constantly on-boarding or terminating external partnerships and expanding or reducing third-party services, it’s therefore important for business leaders to develop a strategy and road map to systematically identify third parties using an inclusive definition.

For many companies, key data about business relationships resides in multiple procurement systems and in emails, spreadsheets, and text documents. Manually building a complete inventory of current contracts from these multiple sources, and then analyzing and interpreting all the data in order to assess risks and make informed decisions can prove challenging.

New technologies such as robotic process automation and natural language processing can however help obtain visibility over third-party relationships. RPA helps integrate information from disparate sources and systems without manual intervention and embed control mechanisms into an automated process, thus increasing efficiency and streamlining third-party transaction risk management.

On the other hand, natural language processing helps to analyze documents written in plain text and signal critical risks, enabling third-party controls to be automatically reviewed for potential risks emanating from inadequate or unclear contract language.

Strong governance process

Traditionally, risk has been regarded as something to be minimized or avoided, with considerable effort spent on protecting value. However, in today’s global competitive environment, in order to progress and achieve strategic success, a business should develop an appetite for risk taking. A business cannot expect to grow and expand by avoiding risk or hesitating to expand its universe of third-parties.

However, given that today organizations are being held responsible not only for their own actions but also for the actions of customers, suppliers, vendors or partners, it’s critical for company boards to provide oversight to ensure that effective third-party risk management practices are in place.

To avoid confusion, there should be clarification on who owns third-party risk in the organization, including where third-party risk management sits within the organization. It is the board’s responsibility to ensure that management establishes a clear organizational model and process for third-party risk management.

In addition, management should provide a clear line of sight to the organization’s major external-party risks by establishing an effective reporting system and keeping the board informed of how critical risks will be mitigated.

The focus should not only be on achieving cost savings or efficiencies, but also on driving value creation and meeting set objectives of the business. Thus, there should be alignment to the broader strategy of the business.

As the world increasingly becomes digitally interconnected and the extended enterprise grows and gets more complex, third-party risk management should also become a top priority for any business.

Also important to note is that assessing and mitigating third-party risk is an ongoing process. It’s about prevention rather than reaction.

Human or Machine Intelligence? Augmentation Key to Better Forecasting

Forecasting is an invaluable process for any business. A forecast can play a significant role in driving company success or failure. For example, high forecast accuracy helps a business anticipate changes in the market, identify growth opportunities, reduce risks, analyze  root causes of performance and proactively respond.

On the other hand, forecasts that are poorly designed, based on weak assumptions often result in unintended consequences.

Preparing highly accurate and reliable forecasts to support decision making is one of the major challenges faced by performance management teams across sectors and industries.

Traditionally, business performance forecasters have relied on past performance to predict future performance. In a perfect, static world the formula works well. However, as we all know the world is not static. The only thing that is constant is change.

Volatility, uncertainty, complexity and ambiguity are at an increasingly alarming level. Further, new technologies are transforming how we do our work now and in the future.

A number of manual processes have successfully been automated. Where businesses have previously relied on financial data alone to make strategic decisions, the dawn of the digital age has brought new meaning to non-financial data.

The new world of algorithm-powered machines

The traditional approach of forecasting is highly manual and time-consuming. People spend a significant amount of time gathering, compiling and manipulating data in spreadsheets.

Most of the time, the data used to predict the future and create forecasts is historical financial data residing in the company’s ERP systems.

Unfortunately, in today’s rapidly changing world the future doesn’t sufficiently resemble the past.

As the new digital era continue to unfold, more and more data (financial, operational and external) will increasingly become available to support business forecasting.

Given that the traditional approach of forecasting leverages data in structured format to prepare forecasts, with more and more unstructured data available, CFOs and their teams have to rethink the old school forecasting process.

In order to increase the agility of the business to proactively respond to competitor activities, customer, market and industry changes that threaten the achievement of set objectives, or trends that present specific opportunities, the organization should consider all types of data at its disposal and discern what is important and what is not for business performance forecasting purposes.

Artificial Intelligence, machine learning, deep learning and natural language processing are disrupting traditional business operating models and companies are increasingly tapping into these new technologies to drive forecasting processes. These highly powered machines use statistical algorithms and modern computing capabilities to collect, store, and analyze large quantities of data and predict what is likely to happen in the future.

The algorithms are fed with warehouses of historical company and market data and taught to mimic human intelligence. Overtime, through learning, forecasting accuracy is improved.

In addition, NLP algorithms are able to go through a myriad of documents including articles, social posts and other correspondences written in plain text and extract insights that can be injected into the forecasting model.

Humans and machines augment each other

It is no secret that machines have a superior advantage over humans when it comes to collecting, storing and analyzing large data sets in real-time. But does this imply that decision makers should rely exclusively on machine intelligence to drive business decision making? The simple answer is no.

When it comes to applying critical thinking and judgement, human beings are much better than machines. Humans are able to evaluate and translate the machine’s conclusions into decisions and actions. Take for instance the forecasting models that are used to predict the future, the best source of information for these models are the domain experts for whom the models are designed.

The domain experts have a better understanding of the models, what assumptions to base the models on including the ability to uncover flaws that others may miss. Software developers, data scientists, AI experts and automation engineers, among others rely on expert judgement of domain experts to hard-code data features in databases that are used to train predictive algorithms.

In one of my articles, Applying Design Thinking to Finance, I highlighted how companies are heavily dependent on analytical thinking in order to drive business performance.

The solution is not to embrace the randomness of intuitive thinking and avoid analytical thinking completely. The solution lies in the organization embracing both approaches, turn away from the false certainty of the past, and instead peer into a mystery to ask what could be

The fact that the past is not a reliable predictor of the future does not necessarily mean that it is not important. History has been known to provide major lessons to us. In the same manner, human judgement can be used to determine which historical data is suitably representative of the future to be included in forecasting decisions.

When data is abundant and the relevant aspects of the business world aren’t fast-changing, it’s appropriate to lean on statistical methods to prepare forecasts. However, even after the forecasting model has been designed and adopted, human judgement is still required to evaluate the suitability of the model’s prediction under different scenarios.

Important to note is that predictive models do no more than combine the pieces of information fed to them. These machines are good at identifying trends and imitating human reasoning. If bad or erroneous data, or good but biased data is presented to the algorithms, issues can arise.

Setting aside human biases

People make decisions based on logic, emotion and instincts. One of the challenges of preparing forecasts in a complex and constantly changing world is setting aside human biases.

Subconsciously, human beings have a tendency to base judgement and forecasts on systematically biased mental heuristics rather than vigilant assessment of facts. System 1 Thinking.

According to Daniel Kahneman in his book Thinking Fast and Slow:

  • System 1 is an automatic, fast and often unconscious way of thinking. It is autonomous and efficient, requiring little energy or attention, but is prone to biases and systematic errors.
  • System 2 is an effortful, slow and controlled way of thinking. It requires energy and can’t work without attention but, once engaged, it has the ability to filter the instincts of System 1.

Personal experiences built overtime make us overgeneralize facts and jump to conclusions. Instead of focusing on both existing and absent evidence, we act as if the evidence before us is the only information relevant to the decision at hand.

As a result, the risks of options to which we are emotionally inclined are downplayed, and our abilities and the accuracy of our judgement are also overestimated.

Further, a focus on the limited available evidence causes us to create coherent stories about business performance including causal relationships that are non-existent. We are quick to ignore or fail to seek evidence that runs contrary to the coherent story we have already created in our mind.

Such actions do not result only in overconfident judgement but also cause us to be overly optimistic and create plans and forecasts that are unrealistically close to best-case scenarios.

By addressing own cognitive biases and enabling collaboration between humans and machines, business forecasters will be empowered to create forecasts that enable faster and more confident decision making.

Machines can only assist and not displace the typically human ability to make critical judgement under uncertainty.

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