70% of leaders in financial services said that the speed of change in technology was concerning. The time needed to go from breakthrough technology to mass market application, in particular, is decreasing rapidly. The telephone that we all take for granted today took about 75 years for half the population to integrate into their lives. In contrast, the smartphone that we all have and cannot leave our homes without achieved the same feat in under a decade. We are witnessing a blockchain move from a simple notebook sketch to an established technology in a fraction of the time it took for Internet to be widespread.

The future of finance for medium-sized enterprises is filled with high quality data enabled by technology as well as a continuously upskilled finance talent pool. Absolute costs will be lowered as work shifts towards more value-added activities as opposed to transactional ones. Comprehensive Big Data will guide top level decisions, and finance operating models as well as finance corporate centres will need to be reimagined.

Shift in focus from transaction processing to value-added activities

Leading organizations have increased their level of efficiency in transactional functions by 39% or more. This includes functions such as accounts payable, accounts receivable, and other core accounting tasks. While most companies still have room to improve, further efforts pumped into increasing efficiency will likely reap diminishing returns as the cost base for these activities shrinks.

In contrast, there are large efficiency gaps in other comparatively more strategic areas of finance such as Financial Planning and Analysis (FP&A), financial risk management, tax planning, capital structure optimisation, controllership, strategic planning, treasury, policy setting and more. Finance leaders only spend 19%1 more time on these aforementioned value-added activities versus transaction-processing activities than a typical finance department did.

Hence, it is evident that the future of finance will prioritise value-added activities. After all, today’s finance leaders spend more of their finance staffs’ bandwidth on value-added activities than the average company did ten years ago. Firms will need to deepen their capabilities in value-additive areas to create a positive feedback loop that promises greater competitive advantages in future.

Reduced costs and better resource allocation through technology

Technology has enabled major advances in computing power, machine learning and artificial intelligence (AI). These advancements have been increasingly applied to complete complicated tasks. Transactional activities, for instance, have been automated with Robotic Process Automation (RPA) and other similar technologies.

One high-tech manufacturer employs machine learning algorithms and analytics to monitor business continuity and financial risks. With audits consolidating their focus on items posing the greatest threats, staff time needed for each audit has been greatly reduced. By extension, the cost of internal audits have also gone down by 15 to 20%.

Likewise, a global consumer packaged goods firm used Natural Language Generation (NLG) to create an initial draft of the management discussion and analysis for a monthly operational review. By converting structured data gathered into meaningful financial prose that summarises and synthesises insights, parts of the report can be automatically churned out. This frees up time of highly skilled finance employees to work on other risks and grab other higher value opportunities.

Another firm runs restaurants in an airport and faces the issue of reimbursing meal voucher claims from airline companies during flight delays in a time-consuming manual way. To combat that, it implemented a scanning system that allowed frontline staff to automatically capture details from customers’ boarding passes. This streamlined a number of finance and operational processes, as well as reduced human error. The data is more standardised since it is electronically captured, and is also more timely and accurate. Employees on-site spent less time repeating unproductive manual tasks such as making copies of documents. The company also had an e-procurement system that processed at least 30% more invoices over three years.

As evident from the above, the trade-off between cost reduction and increased effectiveness of a finance function is a false choice – You can reduce cost while increasing efficiency. To excel, you need to create value and demonstrate stewardship by lowering costs and shifting work towards more value-added activities.

Data-driven and skilled finance workforce

The rise of big data generated a strong demand for workers equipped with analytical skills such as data scientists, data engineers and data analysts. With talent demand outpacing supply as well as the promise of a relevant and high income career, more and more individuals in the finance workforce are upskilling themselves.

The post-COVID-19 world has also triggered employees to reskill. Consumer banks, for instance, needed to cross-train its employees specialising in specific services as demand for mortgage-refinance applications surged. They also trained soft skills such as empathy to better aid distressed clients on how to use digital tools and new services.

Companies no longer focus on mature and first-wave automation approaches like the RPA. Instead, they are looking at other high-end automation relating to machine-learning or other similar ‘second-wave’ technologies to perform tasks such as capital allocation and financial strategising.

Although 23% of organisations still employ spreadsheets as a primary support for finance business partner activities, 10% are using reporting and predictive tools. We also see this trend rising.

Such advanced processes and a skilled work force build an environment that is prime to unlock efficiency in multiple areas of finance.

Comprehensive and integrated data 

Large and complex data without interpretation has no value. According to McKinsey & Company’s Finance 2030 report1, the total amount of data worldwide is expected to reach 175 zettabytes, or 175 billion terabytes, by 2025. This represents a 66% annual growth rate over 2018 levels.

The exponential increase in data will affect finance professionals. As they strive to build competitive advantages and remain compliant, they will continuously need to distil bigger and more complicated data sets into a single source of truth. Only then can senior management gain actionable and comprehensive insights. 

To achieve this, finance departments require a guided master data management strategy to first collect, then store, transform and interrogate all data. The finance team can support the business through utilising the data warehouse for topics such as  financial-scenario planning,capital and  liquidity management, or assets allocation.

Improved and advanced decision-making

Finance departments are often required to use advanced analytical techniques in addressing urgent business issues.

A case in point will be a North American consumer goods company that is building a forecasting tool that scrutinises variables such as demographics, macro-economic circumstances, geographical factors, and more to determine ideal prices at any point in time. Another regional energy company improved its profitability and liquidity with the use of FP&A in areas like budgeting and forecasting. Its success lies in the use of a what-if analysis prior to solidifying key decisions. 

Beyond providing the above analytical insights, a finance department is also responsible for framing discussions on company performance and providing possible actions to improve it. At the end of the day, insights need to not only be rich, but comprehensive and fast. This also requires deep human expertise to rectify overly optimistic forecasts, or to tweak unnecessarily conservative ones.

Reimagined finance operating models

With COVID-19, finance organizations are catalysed to work on an operating model that allows staff to adjust dynamically and concentrate on the most pressing matters.

To make operational tasks efficient, the new finance operating model has a lean core with tight data standards, stringent data management protocols, enhanced automation, and strong integration with other related digital technologies.

Implementing this model is not an easy task, to say the least. For many organizations, it requires the gradual breakaway from hierarchies underlying firms, and a support towards teams with a flatter structure. It may also involve mobilising temporary teams to deliver insights into business problems, as well as facilitators to enable senior management buy-in and role modelling.

Lean finance corporate centres

Research shows that the extent of leanness in the corporate center is an indicator for overall efficiency in the general and administrative (G&A) functions. This is because corporate center leanness is contagious as their functions are typically both physically and operationally close, with leaders regularly sharing space and information. As a result, leaders may rely on the same approach to steer all functions towards efficiency.

The gravitation towards being lean is something that medium-sized enterprises already have an advantage and experience in. Given their small size in comparison with large Multi-National Companies (MNCs), medium-sized ones do not usually have the luxury of resource abundance. 

Simply put, this means that a change implemented by the corporate centre, of which the finance function is often a substantial part of, can spread quickly across the entire firm. 

An exciting outlook for SMEs

All these trends suggest that medium-sized enterprises can afford to cast a wider net for new efficiency opportunities in their finance operations. Finance can take a key role in managing data, whether consolidating, simplifying, or controlling the vast amounts of information flowing company-wide. SMEs can also strengthen and smoothen their decision making process through adoption of data visualization, advanced analytics, and debiasing techniques. The reimagination of a lean and flexible finance operating model can also foster new skills and capabilities.


  1. https://www.mckinsey.com/business-functions/operations/our-insights/finance-2030-four-imperatives-for-the-next-decade
  2. https://www.pwc.com/gx/en/financial-services/assets/pdf/technology2020-and-beyond.pdf 
  3. https://www2.deloitte.com/content/dam/Deloitte/uk/Documents/finance-transformation/deloitte-uk-finance-business-partnering.pdf
Frank Stevenaar
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