Take The Guesswork out of Optimizing your Processes

Process optimization is the systematic approach of identifying and eliminating inefficiencies within an organization’s flow of work. The main goals of process optimization are to improve business performance and reduce costs by streamlining operations. While the concept seems straightforward, in practice, it often involves significant trial and error. However, by embracing a data-driven approach, organizations can transform process optimization from a guessing game into a strategic advantage.

More often than not, organizations struggle to make the most of the data they have and are overwhelmed with where to begin. While some organizations are further along on their data-driven journeys, many have yet to fully realize the impact this can have in achieving not only organizational success but also providing a competitive edge.

As businesses look to accelerate their AI priorities (and AI investments) in the coming months and years, many will turn to process optimization as a means of prioritizing opportunities to increase productivity, improve product and service quality, enhance customer experiences, and reduce costs.

What it Takes and the ROI That it Can Provide

So how, then, should organizations be thinking about process optimization as a lever to take their business to the next level?

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The answer: be more data driven. Data serves as the backbone of AI and is the cornerstone of effective process optimization – it provides insights into how processes function, identifies areas for improvement, and measures the impact of changes. Specifically, organizations can harness data for Process Optimization to aid in:

How to Mobilize Process Optimization

This brings me to my next point - data must be linked to process optimization to uncover opportunities and value - otherwise, it is just a lot of disconnected information.

Here are steps organizations can take to activate their journey:

Overcoming Process Optimization Challenges

Some of the most common hurdles global enterprises face in their efforts to optimize include cultural resistance to change, unreliable analysis due to data quality, and resource constraints.

When optimizing work, there are sophisticated tools that can assist that should not be overlooked. For example, business process management (BPM) software can aid in automating and managing complex processes, and data analytics tools can provide insights into performance and identifying improvement opportunities. And, when generative AI is incorporated into the mix, routine tasks can be automated, workflows can be optimized, and organizations can better predict outcomes.

It is worth noting that the vast majority of organizations report more success with process optimization than challenges.

Example 1: Healthcare

A study published in the Journal of Healthcare Management highlighted the use of data analytics to optimize patient flow in emergency departments. By analyzing patient arrival patterns, wait times, and resource utilization, hospitals were able to improve patient satisfaction, increase capacity, and reduce wait times. Specifically, the National Health Service (NHS) in the UK saw improved patient care through a decrease in hospital visits by 53% and an estimated £2.8 million pounds worth of savings.

Example 2: Public Sector

After investing in technology-enabling process optimization, the State of Oklahoma obtained data-driven insights that helped it understand its key financial challenges and how to address them. As a result, the State has been able to identify over $174 million in potential savings, complete audits 200x faster, and review more than 24,000 POs worth $4.58 billion in less than 12 weeks.

A Final Word on Process Optimization

Process Optimization is not a ‘set it and forget it’ activity. Instead, it should be viewed as an ongoing journey. By fostering a culture of continuous improvement, organizations can adapt to changing conditions and maintain competitive advantage.

By becoming a more data-driven organization and leveraging the right data and technology partners, organizations can significantly enhance their processes, reduce costs, and drive overall success. The key to success lies in a continuous improvement mindset and the active involvement of employees at all levels.