Cycle Time: The metric all businesses should use to drive continuous improvement

Cycle time is a relatively simple metric that’s widely used to measure and improve the efficiency and productivity of business operations. Consistently monitoring cycle time is also an effective way to quickly identify operational issues, enabling them to be addressed before they have a sizable impact on customer satisfaction or profitability.

The way cycle time is calculated and applied varies greatly between industries and functions, but all businesses should consider it a critical KPI to build operational resilience and remain competitive in their market.

What is cycle time?

Cycle time is simply the total amount of time it takes to complete a process, from start to finish.

The concept of cycle time comes from lean manufacturing, where it refers specifically to the production time for one unit or item. But the metric has been adopted across many other sectors and business functions — from finance to customer service to project management — and its definition varies depending on the process to which it is applied.

Examples of specific cycle times include:

• Invoice processing cycle time: the amount of time from invoice receipt to payment transmission.
• Customer onboarding cycle time: the amount of time it takes to complete the customer onboarding process.
• Sales cycle time: the amount of time from the first touch with a potential new customer to closing the deal.

Celonis helped RATIONAL reduce sales cycle time for blocked orders by 40% — increasing process efficiency across sales and customer service and delivering a better customer experience.

Cycle time differs from takt time and lead time

Because cycle time originates in lean manufacturing, it is frequently confused with other metrics that are also used in production — and these are takt time and lead time. While there are some similarities between these measurements, they each have a specific definition and aren't usually interchangeable.

Takt time is specific to production and is the speed at which products need to be manufactured to deliver what’s been promised. This means it fluctuates with customer demand. For manufacturers to satisfy customers, cycle time needs to be the same as takt time, and should ideally be less than average takt time to allow for peaks in customer demand.

Lead time refers to the total time between an order being placed and the customer taking delivery of the finished goods. In manufacturing, lead time tends to be cycle time plus the time between an order being placed and production beginning, plus delivery time. Lead time is different from ‘order cycle time’ which doesn’t include delivery time. It is useful as an indication of how long the order process takes from the customer’s perspective.

How is cycle time calculated?

In manufacturing, there’s a standard cycle time formula. It’s net production time (NPT) — which is the time spent actually producing the items excluding any breaks, meetings, or other downtime — divided by the number of units produced.

Manufacturing cycle time = Net production time (NPT) / Number of units produced

But when cycle time is used to measure other processes, and across other industries, using this production cycle time formula isn’t necessarily helpful. For a start there may not be multiple units being produced. But more importantly, it’s usually more representative to include wait time and delays in the calculation so businesses can see how long a process actually takes.

Outside of manufacturing, cycle time is usually made up of two elements:

1. Process time: Actively performing tasks to move the process forward.
2. Wait time: Waiting for other events to occur before moving to the next step.

When cycle time is used to measure processes in a non-manufacturing setting, it is usually calculated as the calendar time from the start of the process to the end. This can include multiple steps such as preparation, setup, execution, review, delivery, and completion, as well as any delays between these steps.

An invoice processing example

As an example, according to APQC, the average invoice processing cycle time (from invoice receipt to payment transmission) is 15 days. But that doesn’t mean the accounts payable (AP) team is working on that invoice non-stop for more than two weeks. The team will be working on multiple tasks concurrently, and waiting for input from other teams, so there will be days during that period where the process doesn’t progress at all.

When something happens to disrupt invoice processing, it will add to the cycle time. For instance, if a payment block is set it could potentially add three days. But again, that doesn’t mean the AP team is working round the clock for 72 hours. Those three days probably include the time it takes for the invoice to reach the top of someone’s to-do list, the time it takes to investigate the payment block, and the time it takes a manager to approve the payment or remove the block.

Knowing the actual number of days from invoice receipt to payment transmission, rather than the number of hours the team physically worked on processing the invoice, is important to avoid late payments. This means the business can take advantage of any available cash discounts, avoid late payment penalties, and prevent damage to supplier relationships.

Calculating cycle time by use case

The actual calculation for measuring cycle time will vary depending on the use case. For instance:

• Supply chain cycle time will usually start at the beginning of the ‘supply and make’ stage of the process, include the ‘distribution’ stage, and finish at the end of the ‘fulfillment’ stage. Find out more about supply chain cycle time by watching our on-demand webinar.
• Software development cycle time is often designed to isolate the delivery phase of the software development process, and measure the amount of time where the code is in progress. This could mean, for example, the time between a developer’s first commit in a section of code and when that code is deployed.
• Deviation management cycle time is used in the pharmaceutical industry to ensure quality control and compliance. It measures the time it takes to evaluate deviations from defined pharmaceutical processes, including testing of additional batches. Celonis helped Vetter Pharma achieve a 15% reduction in deviation management cycle time.

Consistency is key to cycle time calculations

In essence the cycle time formula you use doesn’t matter as long as it makes sense for your unique business processes, and it’s applied consistently across your operations so you can measure trends. Want to look at the time it takes to process an invoice in two different countries, or compare the throughput time of a purchase order between two different suppliers? Having a consistent approach to cycle time calculations allows you to do just that.

Continuously monitoring cycle time means any changes can be used to either quantify process improvements and productivity gains, or to flag potential issues that may need to be resolved. Whatever calculation you use, it’s vital to measure the amount of time a process actually takes, rather than the time it is expected to take, to get an accurate view of where improvements can be made.

How process mining improves your cycle time

Process mining helps businesses to optimize their operational processes, reducing cycle time and unlocking hidden value. It’s a bit like an MRI that shows how business processes actually run, not how you think they run.

Process mining shows all of the different paths being taken from the beginning of the process to the end. It then takes the desired path — which usually has the shortest cycle time — and compares the different variants with it to see where the differences are and identify value opportunities.

Check out our demo to discover how a manual change of purchase order price (which is a very common deviation from a standard process) can prolong cycle time by up to nine days, having an enormous impact on productivity and efficiency.

The information generated by process mining can be used to develop strategies for reducing cycle time, including:

• Standardization: Reducing variations to ensure that processes are being executed in the same way across the organization.
• Streamlining: Reducing the number and complexity of the steps in a process.
• Optimization: Adjusting the process to optimize it for a certain KPI, like cycle time.
• Automation: Reducing human effort, and potential for error, by automating steps within a process workflow.

Cycle time reduction in action

Let’s take a look at some of the ways innovative businesses are using Celonis and process mining to reduce their cycle times:

Accenture improves request-to-order cycle time by 50%

Globally-renowned professional services company Accenture uses process mining to gain visibility into the whole purchase-to-pay value chain, from procurement to AP.

By identifying areas for improvement and eliminating a number of unnecessary steps, request-to-order cycle times were reduced from 30 hours to 15 hours, delivering a faster and more efficient experience for consultants, and ultimately Accenture customers.

Credibom sees a 5% to 10% improvement in overall cycle time

Consumer bank Credibomuses process mining to streamline its operations in the areas of consumer solvency analysis, loan financing, and fraud detection.

Focusing on the time it took to get to a yes decision, time to cash, first time right, rework rates and abandon credit files rate, Credibom saw a 5% to 10% improvement in overall cycle time, and removed more than 10,000 rework activities from its processes.

Tech Data cuts procure-to-pay total cycle time by 57%

Technology distributor Tech Data uses process mining to identify improvement opportunities in areas such as procure-to-pay, order-to-cash, and after sales management.

Achieving a 57% reduction in procure-to-pay total cycle time within a year enabled Tech Data to ensure customer satisfaction while also cutting down on operational costs.