Businesses become more efficient and agile due to business process automation (BPA), in which technology such as virtual agents or cognitive engines incorporated into software take over regular operations. BPA projects have taken off in recent years, propelled by CEOs whose firms are on the fast route to digitization—or who want to free up their workers for more creative, high-value endeavours.
BPA is not a single technology or endeavour. Rather, it is a continuous process of employing technology to automate manual activities, hence removing humans from the picture partially or entirely. Most businesses begin with smaller duties, such as first-line customer service or T&E (travel and expenditure) routing, and move from there as employees gain experience.
Companies may now automate practically any horizontal business function, including planning, profit forecasts, branding, ERP, CRM, customer service, and HR, thanks to more powerful software workflow engines. Similarly, increasingly advanced AI and machine learning, big data, and robotic process automation (RPA) technologies enable fascinating vertical BPA initiatives in certain industries.
Let’s take a closer look at some of the more potential regions.
Market for Automation
At least one function in 31% of organizations has been automated. —McKinsey
However, the percentage of businesses that have completely automated at least one function has increased more slowly, rising from 29 percent in 2018 to 31 percent in 2020.
McKinsey notes that common themes across firms that have successfully completed BPA programmes include including staff in educating the automation systems and erring on the side of over-communicating: “Respondents from organizations that have successfully implemented automation initiatives are seven times more likely than others to say they formally incorporate the communications function while adopting automation efforts, and they are more than twice as likely to say the HR department is involved.”
Business Process Automation vs Business Process Management
Business process automation (BPA) and business process management (BPM) are connected but not interchangeable terms. BPM is a business approach that entails a defined organizational technique based on a predetermined path for the efficient and effective administration of all processes.
Only 2% of the firms questioned have modelled all of their business processes, whereas 62 percent have modelled up to 25% of their business processes. —Signavio
According to the Association for Information and Image Management (AIIM), implementing BPM successfully necessitates organizing outcomes and standardizing processes. Before automating the process, BPM improves them—an important step to avoid merely transferring defective procedures from human to automated executions.
While BPM is a business strategy, people who utilize it model their processes with specialist BPM tools before optimizing, automating, and measuring them. In truth, when it comes to repeating tasks that require some decision-making, “automation” is the operative term.
BPA complements and is interdependent with other forms of automation that are gaining traction:
- Bots are used in robotic process automation (RPA) to replicate routine cognitive human functions. According to Grand View Research, the RPA market, valued at $1.4 billion in 2019, is expected to increase at a CAGR of 40.6 percent between 2020 and 2027.
- Digital process automation (DPA) is a newer variation of business process management (BPM) that is far lighter and requires less coding. DPA was a $7.8 billion market in 2019; Mordor Research predicts it will expand at a CAGR of 13%, reaching $16.12 billion by 2025.
Demand planning, the process of precisely predicting which commodities consumers will order and in what amount, is critical to efficient supply chain management (SCM). Underestimating demand results in lost revenue and disgruntled consumers, whilst overstating demand results in excess inventory.
Weather, the economy, tariffs, currency changes, and many other interruptions can influence demand projections. Some can be accounted for by successful product portfolio management and forecasting, but manual estimations are time-consuming.
Modern ERP systems, for example, feature SCM automating capabilities that allow for real-time demand planning decision-making. AI, machine learning, predictive analytics, and the usage of sensors have all helped to improve visibility.
One large logistics company, for example, implemented a demand forecasting system and was able to generate 35 million forecasts using data from 2,000 sites. Forecasts throughout the four-week study had an accuracy rate of 88 percent, according to a study performed by consultancy firm Elder Research.
Accounting software’s revenue recognition automation features are designed to take the guesswork out of collecting and computing when revenue is recognized. Automating revenue recognition cycles not only simplifies the process but also lowers the risk of frauds and errors, ensures compliance, and accelerates decision-making by delivering data in near real-time.
It is about to become extremely critical. Whilst Financial Accounting Standards Board (FASB) has extended the deadline for non-public enterprises to comply with ASC 606 until December 15, 2021, more regulations are on the way. The move is designed to make it easier to evaluate revenue recognition procedures across companies, industries, jurisdictions, and capital markets while adding more relevant information to financial statements and mandating improved disclosures in financial statements.
Compliance will be relatively simpler as a result of automation. It’s no surprise that the global accounting software industry is expected to grow at an annual rate of 8.02 percent from 2018 to 2026, from $11 billion to $20.4 billion. Companies that do not automate will soon find themselves at a competitive disadvantage.
Time Management and Productivity
Technological investments, including automation, aim to increase worker productivity. However, the outcomes have been mixed.
As per the Bureau of Labor Statistics, productivity growth in the United States was only 1.4 percent between 2007 and 2019. Since the economic meltdown, growth in the manufacturing sector has only increased by 0.5 percent, down from 4.4 percent.
There are underlying difficulties that are impeding output. Here are a few things to think about:
- According to Gallup, high-performing employees share three characteristics: talent, strong engagement, and a 10-year or longer tenure with their companies.
- According to Deloitte, 43 percent of Millennials plan to leave their existing job within two years, while only 28 percent plan to stay longer than five years.
- According to consultancy Korn Ferry, 85 million positions could be unoccupied globally by 2030 due to a lack of skilled workers. It might result in unrecognized annual revenues of $8.5 trillion.
- According to Statista, the productivity software industry, which comprises office and collaboration apps, is expected to reach roughly $62 billion in 2020, with revenue expected to grow at a CAGR of 6.8% to $85 billion by 2025.
By transferring to technology the types of monotonous jobs that restrict employees from taking on more exciting work or committing time to training and development exercises that may raise productivity, automation projects might lead to increased engagement.
According to McKinsey, at least one among weekday activities might be automated in around 60% of occupations. Make automation a part of the debate when it comes to productivity and time management, payroll, tax compliance and reporting, and accounts payable. Your workers will thank you—a recent ServiceNow poll of over 6,000 knowledge workers found that BPA increases performance and satisfaction.
And the more intelligent this technology becomes, the higher it rises in the work stack.
Machine Learning & Artificial Intelligence
Machine learning and artificial intelligence advancements are important enablers of BPA. While many individuals mistakenly use the terms interchangeably, this is not the case.
AI is an umbrella term for the science of developing intelligent software, bots, and machines that can perform decision-making and problem-solving tasks now handled by people.
Machine learning is one of several subsets of AI. Still, it is the most important since it uses algorithms and neural networks to collect huge amounts of data, including telemetry from monitors and other endpoints, to make choices and perform tasks.
Natural language processing (NLP), RPA, virtual agents (conversational interfaces), autonomous cars, and human-like robots are all examples of fast-maturing ML and AI-driven automation. Financial services are one industry that has been quick to incorporate AI.
According to McKinsey’s 2019 Global AI report, genuine AI adoption in BPA is still very low, while it has accelerated significantly over the years, with business AI adoption up 25%.
The following are some of the significant findings:
- Sixty-three percent of those who have used AI feel it has resulted in higher revenue.
- In 2019, 58 percent of respondents said they had integrated at least one AI component into a product or a process, up from 47 percent in 2018.
- AI was used in 30 percent of business units, up from 21 percent the year before.
Many corporations hastened their AI implementations as the COVID-19 outbreak of 2020 unfolded. McKinsey performed a separate study three months following the outbreak. Half of the 800 executives were all from the U. S., while the rest came from seven different nations.
Since the epidemic, 88 percent of financial and insurance executives and 76 percent of IT executives have advanced their automated and artificial intelligence initiatives. Before the epidemic, these businesses were already pioneers in the automation and digitization of processes. As a result, businesses in these industries were in a good position to speed their deployments.
Respondents chose the following as the Top 9 AI benefits:
- Improve the quality of your products and services: 43% of people
- Internal business activities should be optimized: 41% of the population
- Make more informed decisions: 34% of the population
- Automate jobs to free up time for staff to be more creative: thirty-one percent
- External processes have been improved: thirty-one percent
- Produce new items: 12%
- Investigate new markets: 30%
- Capture and utilize the knowledge that might otherwise be difficult to obtain: 12%
- Reduce staff by 24 percent by using automation.
Automation & Workflow
For decades, businesses have used systems to automate business procedures, but AI now enables regulations engines to replace manual approvals by automatically triggering events.
Machine learning is used in modern workflow management solutions to improve how firms automate procedures, including approving sales discounts, allowing staff travel and entertainment charges, and effectively responding to customer enquiries. Because of digitization and a focus on optimizing company operations, demand for modern workflow automation management systems is expected to grow at a CAGR of 27.7% through 2025.
Introducing technology to the supply chain is one of the most popular projects.
According to a survey published in late 2019, the supply chain AI industry would develop at a CAGR of 39.4 percent through 2027. But, just months after the COVID-19 epidemic, Meticulous Research boosted that projection to a staggering 45.3 percent, predicting that the market would reach $21.8 billion in much less than seven years.
The capacity to gather all relevant data throughout a business process is critical to BPA success. Because of the complexity of some operations, the ability to digest enormous amounts of organized and unstructured data—big data—is required.
Companies may now trust automated decision-making because of advancements in the big data processing.
Big data also serves as the foundation for AI, at the heart of advanced BPA projects. According to a recently executed survey conducted by New Vantage Partners,
- In 2020, 65 percent of companies intended to spend more than $50 million on big data and AI initiatives, up 40% in 2018.
- While just 38% have established data-driven organizations, 27% have succeeded in establishing “data cultures” within their enterprises.
- The biggest roadblocks to becoming data-driven enterprises, according to 91 per cent of respondents, are personnel and process issues.
That’s probably something CFOs can connect to.
Robotic Process Automation (RPA)
RPA uses software-based robots, also known as “bots,” to automate recurring human processes
Each bot performs a task that a human previously performed after being built with machine learning and rules engines. While many of us think about RPA in terms of customer care chatbots, it’s also used to automate financial reporting tasks.
According to Gartner, RPA might save finance teams 25,000 hours of unnecessary rework due to human errors, saving them $878,000. Despite this, just 29% of chief accounting officers (CAOs) polled use RPA for financial reporting, according to research.
The analytical group expects that the global RPA market would expand 19.5 percent to over $2 billion from 2019 to 2020, according to the report:
- By 2022, 90 percent of large enterprises worldwide will have implemented RPA in some form.
- Organizations’ existing RPA portfolios will be tripled in capacity.
- Business managers will acquire half of all new RPA customers rather than IT.
- By the end of 2020, RPA software prices will have dropped 10% to 15%, with another 5% to 10% drop in 2021 and 2022.
It means that now is an excellent time to learn more about the technology. For pilot studies, CFOs may want to collaborate with the managers of marketing and HR.
Automation in Human Resources
Human resources management system is gaining popularity around the world. Modern cloud-based HRMS, also referred to as human capital management (HCM), utilizes data to model it from salaries and benefits to employee performance and labor allocation. According to a forecast by Gallagher, an insurance brokerage, risk management, and consulting organization, investments in HR technology will skyrocket between 2020 and 2022.
By 2022, more than two-thirds of HR executives polled (69%) want to enhance or replace existing HR systems. The following are the findings:
- Only 15% of companies have comprehensive HR technology strategies that align with their company objectives.
- Despite this, 35% of companies have successfully deployed new HR technologies since 2018.
- Over 75% of the capabilities given in their systems are used by 29% of respondents.
Littler conducted a poll of HR experts and C-suite executives and discovered that businesses are not reaping the full benefits while AI is being used to filter applications. The majority of respondents, 69 percent, said they do not use these tools in their recruiting or hiring processes.
That was a blown opportunity. The top HR technology issues in PwC’s 2020 HR Technology Survey were attracting and retaining top talent, developing individuals to reach their full potential, and automating chores to improve the work environment, all of which AI can help with.
Companies appear to be paying attention: 74 percent of the 600 HR and IT executives polled by PwC intend to boost HR technology spending. By the end of 2020, 72 percent of respondents expect their core HR apps to be cloud-based.
The marketing automation software industry will reach $16.87 billion by 2025, with a CAGR of 19%. —Intelligence from Mordor
Marketers are concerned with acquiring new customers, increasing sales from existing customers, and building and sustaining brand recognition.
How this occurs is determined by the company and its customers. Is it better to spend money on traditional advertising through various media or direct outreach through mail, email, the web, and social media?
Companies no longer need to guess or choose because automation and improvements in omnichannel marketing technology have enabled tailored and interactive forms of engagement. They can use marketing automation software to do “all of the above,” automating monotonous operations, assisting marketers in customizing and automating complete campaigns, and providing data and results analysis.
According to Mordor Intelligence’s marketing automation software market analysis, adopters prefer lead collecting and targeted offers.