Lead Time vs. Takt Time vs. Cycle Time: Key Differences

In inventory management, for instance, lead time is the duration between placing a purchase order to replenishing products and storage receiving the order. Order lead times vary by suppliers, and when more suppliers are involved in the inventory management chain, the lead time is typically longer.

The formula to calculate lead time is not universal and depends on various factors. For instance, manufacturing lead time factors in the pre-processing stage (planning), the processing stage (procurement and actual manufacturing), and the post-processing stage (dispatch). The formula can, therefore, be summarized as follows:

Manufacturing lead time = time taken for pre-processing + time taken for processing + time taken for post-processing

Now, let’s go back to inventory management. When calculating lead time here, two factors must be considered: the duration from ordering inventory to receiving it (supply delay) and the wait duration before ordering supplies (reordering delay). Between these two factors, the amount of time taken for suppliers to process and fulfill orders is accounted for. The formula for inventory lead time calculation can, therefore, be summarized as follows:

Lead time = reordering delay + supply delay

Lead time calculators can help determine the right formula for specific use cases. Calculating lead times accurately is useful for setting accurate delivery dates and optimizing the overall process in various ways.

Takt time = available production time/average customer demand

To use this formula, first define production time and customer demand and put them into frames. Account for and exclude planned downtime, as it is recommended to calculate using only the time spent actively working on creating value. Therefore, breaks, shift transitions, and scheduled maintenance must be excluded. Also, it is recommended to use short time frames (one week or one month) for customer demand.

Note that available production time must account for the total production time available for a particular period. On the other hand, customer demand must define the quantity of products or services required by customers during the same period. Figures are usually expressed as a quantity or rate, such as calls per hour, hours per week, or units per day.

For instance, a new product order is received every two hours, meaning a product must be created in two hours or less to meet this demand.

Avoiding overproduction and underproduction is also key — if products are being produced faster than one every two hours, it might be classified as overproducing and lead to an inventory overload. Conversely, failure to produce one product within two hours can lead to failure to meet customer demand.

Cycle time = net production time/number of units produced

The calculation begins by determining the net production time, which is the available time for personnel to finish a specific project. This value is generally measured in hours and enables users to account for processes and delay time during production operations. Net production time is the number derived from subtracting the time spent not working on the project (such as meetings or breaks) from the total time spent working per day.

The next step is calculating the total number of goods produced is the next step. This includes counting the number of units produced during net production time.

Next, the net production time is divided by the total number of goods produced, resulting in the cycle time value. This value must now be converted into time, as it is meant to measure the time taken to complete the work unit. To convert the number in the answer into hours, the user must multiply the decimal portion by 60.

Once the value in hours is ready, it is time to interpret the results by comparing them against the target cycle time. The target value can be determined based on factors such as company goals, the number of employees, and the amount of time employees take to complete tasks.

Finally, performing routine calculations for all metrics is important since they can fluctuate. This helps ensure accuracy and helps optimize production processes.

First, shorter lead times are likely to increase customer satisfaction because, in a fast-paced world, customers are eager to get their product as soon as possible after placing an order.

Shorter lead times may also correlate with less obsolescence. Although this is applicable in rather specific cases, goods with long lead times indeed run the risk of facing obsolescence by the time manufacturing is complete.

A shorter lead time helps reduce labor costs. By prioritizing the review of internal manufacturing processes, companies can reduce inefficiencies and minimize unnecessary labor hours. This helps ensure reduced costs and more efficient labor utilization.

A shorter lead time can result in more order throughput. All other factors being equal, a product with a shorter lead time will likely see higher demand than a similar product with a longer lead time. Companies boasting shorter lead times will likely attract more orders, especially for products with high demand.

Finally, shorter lead times can lead to more efficient capital deployment. Money deployed in raw materials and manufacturing processes must lead to the creation and sale of finished goods before it turns back into money. Therefore, shorter lead times mean a shorter duration without capital for the company.

Companies improve the predictability of related metrics by using takt time to align production and customer demand and reduce waste across processes. Another way to interpret this is “improved efficiency,” as takt time can enhance production efficiency by optimizing production rates per customer demand. Waiting times and other process inefficiencies are thus reduced.

Finally comes the core tenet of takt time: continuous improvement. This metric is a clear target for teams to achieve, allowing them to identify areas of improvement. Progressive improvement of the value creation process allows teams to increase efficiency, decrease costs, and enhance customer satisfaction.

First, shorter cycle times lead to faster delivery and demand fulfillment. By measuring cycle time, users can improve current processes more easily by identifying and addressing friction. Consistently improving workflows helps deliver faster output and establish a healthier production cycle.

Shorter cycle times may also correlate with greater efficiency and flexibility among teams, which helps increase customer responsiveness and cut down the costs associated with changing priorities.

Focusing on improving cycle time also drives teams to optimize their current processes. To mitigate the negative effects on cycle time, teams will naturally limit concurrent work and context switching. Parallelly, an increased focus on smaller chunks of work encourages personnel to speed up processes, streamline them, and establish more efficient feedback loops.

A focus on minimizing defects can also be observed as cycle time optimization takes root within an organization. Shorter cycle times mean a lower probability of mistakes within processes.

And finally, all these improvements help enhance morale. When teams see the time wasted on inefficiencies and start enjoying a more streamlined process, they are bound to have a more positive experience and showcase higher motivation levels.

Another tip is to include lead time design in manufacturing design. By involving stakeholders from the manufacturing and supply chain early in the product development process, design requirements can be tweaked to optimize lead time.

Creating an inventory buffer can also help, as long as it does not lead to overproduction. While holding too much inventory is a negative, pushing supply chains to run on the edge is not always the best way forward either. Striking a balance is crucial.

Yet another best practice to reduce lead time is establishing parallel processes. If one part of the overall process is not dependent on another, both can be executed simultaneously.

Monitoring every process that contributes to the lead time of a task and seeking continuous improvement is an effective strategy. Here, lean methods can help users assess and enhance processes across the product development journey.

Keeping suppliers informed of forecasts for future demand helps them manage their lead time and, subsequently, reduces the client company’s lead time.

Leveraging automation is also a sure-shot way to improve lead times. For instance, Industry 4.0 and robotics technologies can help optimize lead times significantly.

Using software to manage and automate the steps needed to take a product or service to market can also decrease lead time. Examples include a full ERP system or point solutions such as vendor management, accounting systems, and inventory management tools.

Finally, processes separated by distance can increase the time taken and introduce points of failure. Therefore, moving the supply chain closer to home can help decrease total lead time.

Measuring individual cycle times and other metrics helps optimize takt time. For instance, monitoring cycle time and diving deep into its complexities allows companies to plan for periods wherein takt time can be less or greater than the ideal mark. Monitoring this metric helps in the decision-making process regarding scheduling and planning to balance out takt time. Cutting-edge solutions that automatically capture cycle times exist — they help ensure data accuracy and efficient benchmarking. These tools help managers understand and manage takt time better.

Apart from cycle time monitoring, other process metrics to consider for takt time optimization include turnaround time (time from order placement to delivery), efficiency (production time divided by total process time), quality rate (percentage of first-quality parts divided by total produced units), and throughput (units produced divided by production time for each unit).

Another best practice for takt time optimization is removing non-value-added time or waste. Improvement teams must begin by studying and measuring performance attributes and dividing tasks into value-added and non-value-added time categories. Next, non-value-added time must be eliminated from process steps and formalized in the workflow to reduce cycle time. This will potentially lead to lower takt time for the specific period.

Finally, accounting for overall equipment effectiveness (OEE) is another way to monitor and enhance processes. OEE considers availability, quality, and performance. By diving deep into the triggers of downtime, enterprises can enhance their OEE and, in turn, optimize their takt time.

Automation plays a key role in cycle time optimization. For instance, in the case of software development, users can implement a robust CI/CD pipeline to automate integration activities, thus reducing delays. Similarly, E2E test automation can be leveraged to expedite the testing process and avoid manual regressions that reduce the speed of releases.

Developing a system that features ready-to-use components to streamline operations is also an effective tactic for cycle time optimization. Teams can create output with reduced effort and time by using ready-to-go components instead of starting production afresh every time.

Optimizing review processes is also helpful. With robust quality assurance processes, issues can be caught early on. A culture where stakeholders take collective responsibility for quality assurance (at a basic level, at least) helps save valuable time during the actual QA process.

Highlighting work items with notably longer cycle times than the median and investigating the reasons behind such outliers also helps. Process improvements can occur by addressing the issues with these work items.

Dividing larger processes into smaller ones that are more manageable is also good for cycle time optimization. Smaller work items often mean reduced process risk and more efficient execution.

Finally, experimentation can help. Users can define hypotheses, carry out experiments, and measure the outcomes. When stuck, involving an expert consultant might be wise (and profitable).