Business leaders understand the importance of optimizing their processes, but a lack of understanding surrounding application of emerging technologies like AI could hinder progress.
These were among the results of a Celonis survey of 1,200 global business leaders, which found more than 80% of respondents are either already investing in process optimization technology (49%) or plan to in the next 3 years (32%).
Process optimization refers to the systematic review, analysis and improvement of workflows, operations or business processes within an organization using technology and IT strategies.
The primary goal of process optimization is to enhance efficiency, productivity and overall performance by refining existing processes or designing new ones that better align with organizational objectives.
The vast majority (99%) of respondents said it was essential or important to optimize their processes to meet their business objectives, and for nearly nine in 10 respondents (89%), those objectives include unleashing the full potential of AI.
More than a third (38%) of respondents are already using process mining, while a further 32% are evaluating it.
The survey results also indicated senior business leaders recognize the value of optimizing their processes, with 83% seeing process optimization as their greatest lever for realizing value and their fastest lever for change.
Survey respondents also indicated sub-optimal processes are negatively impacting their organizations by costing their departments time and reducing productivity, resulting in missed opportunities to capture value and preventing innovation.
Process optimization was viewed as particularly important in times of economic instability, with respondents recognizing it as one of the quickest ways to reduce expenditure and get cash flow under control.
However, a little under three-quarters of those surveyed (72%) said they are concerned process shortcomings could hinder their AI success.
Dinesh Varadharajan, CPO of Kissflow, explains stakeholders in process optimization technology fall into two primary categories: Business and IT.
“When individual departments seek technology to optimize their specific processes, they typically finance the investment from their own budgets,” he says. “Conversely, when the goal is to enhance processes across multiple departments, the IT department often takes the lead in selecting and implementing the appropriate technology.”
Businesses must audit existing systems, develop a strategic integration plan, pilot the technology, train employees and continuously monitor and adjust the implementation for seamless integration of process optimization technologies.
He says businesses can effectively utilize emerging technologies like AI to drive efficiency and productivity by automating routine tasks, thus reallocating human capital to more strategic initiatives.
“AI can analyze vast amounts of data to identify patterns and insights that can streamline operations,” Varadharajan says. “This strategic use of AI not only optimizes processes but also enhances decision-making and innovation within the organization.”
He points out process mining technologies can help enable organizations to identify inefficiencies and streamline operations effectively, revealing critical bottlenecks and facilitating effective process reengineering.
“Since initial process implementations are seldom perfect, there is a considerable need for ongoing scrutiny and refinement,” he points out. “Process mining technology is instrumental in this regard, enabling continuous monitoring and optimization of workflows.”
Alok Uniyal, vice president, head of IT process consulting practice at Infosys, says even during challenging economic times, companies must make large-scale digital investments to avoid being left behind, while also weighing the need to deliver positive results quickly.
“This, in turn, creates a need for business leaders to balance cost and value,” he says. “To effectively do so, optimization technology can aid in achieving this goal in an efficient manner through the right formula of responsible AI and data mining practices.”
He explains when combined with AI, data opens new possibilities for enterprises to grow and become more autonomous, with better and quicker decision-making.
“Through responsible data mining, organizations can make the data and AI decisions needed to lead to the next innovation, business model, or customer while aligning with the vision of the enterprise,” Uniyal notes.
He points out he’s seeing more prioritization than ever of optimization technology projects being championed at the CEO level.
“CEOs have had to navigate numerous black swan issues over the past handful of years, so this shift tracks as they try to stay ahead of the curve, creating less speculation when it comes to their buy-in on projects where they can not only control the outcome but also better the business,” Uniyal says.