What is a cycle count? (Plus useful methods and examples)
By Indeed Editorial Team
Published 9 July 2022
The Indeed Editorial Team comprises a diverse and talented team of writers, researchers and subject matter experts equipped with Indeed's data and insights to deliver useful tips to help guide your career journey.
If you work as an inventory manager, you can benefit from implementing a cycle count system to assess your organisation's resource stockpiles. This method makes it easier to perform an internal audit without harming general productivity, potentially boosting your firm's profitability as a result. By reading this guide, you might learn how to implement such a system in your own workplace. In the article, we define the term, explain how this process works and outline useful examples of this process.
What is a cycle count?
Cycle counts involve performing repeat auditing checks on your organisation's inventory to ensure that you can account for each item without actually counting them. Using this method, you can select random sample items from an inventory, before roughly calculating how many similar items also exist within it. After carrying out one count, you can note these items on a register and begin this process again, albeit choosing different sample items. As this process continues over time, you can construct a rough picture of the size of the firm's inventory without neglecting other tasks, boosting your productivity.
Commercial organisations can benefit from using this stock counting method, as it allows them to judge their inventories without temporarily ceasing production. They could then continue serving existing or new clients without creating delays, upholding customer satisfaction with their service. This process also makes it easier for your organisation to reduce human error, as your colleagues only assess a limited number of resources at one time. They can then avoid repeating these tasks to compensate for their mistakes, boosting their total productivity as a result.
How does this process work?
You can use varied methods to calculate your organisation's inventory levels. Each process works by creating boundaries to determine both which goods you can include in a sample and the sample's size. Depending on whether you're using specific or random sampling methods, these boundaries' scope can vary. The following section below outlines five methods that you can use to implement a cycle count:
Random sample counting
Random sample counting involves selecting items from a business' inventory on a purely random basis, with every count taking place across a working day. By using this method, you're less likely to generate inaccurate results as you select items from a common sample and without pre-existing bias. As each good has an equal chance of selection, this method can also introduce greater fairness into the sampling process.
In this situation, you could select from two sampling methods: constant population counting and diminished population counting. The former method involves counting the same number of items per count, with items returned to the inventory after the count. This may cause you to select the same item in consecutive counts. Conversely, the diminished population counting method involves excluding items from further counts until you identify every item within your organisation's inventory.
ABC counting involves splitting items into three groups based on how frequently you sell them to consumers or clients. The first section includes items within an organisation's top 20% sales bracket, accounting for 80% of its sales revenue. You can refer to these goods as 'A items'. The second section contains the next 30% of a business' best-selling items. Known as 'B items', these goods account for 15% of total sales revenue. The final group contains 'C items', which make up the last 50% of a firm's inventory, accounting for 5% of its total sales revenue.
As 'A items' provide the vast majority of your organisation's sales income, it's useful to count this group's size most frequently. By taking this approach, you can determine if the firm's inventory includes sufficient supply to meet short-term demand and decide when to next reorder stock from suppliers. Conversely, you typically count 'B items' occasionally and 'C items' irregularly. By using this format, you can prioritise productive items that deliver greater economic benefit, maximising your organisation's profit-making potential.
Control group cycle counting
Control group cycle counting involves building a control group to create a benchmark against which to judge the success of the real counting process. Unlike the actual sample set, independent variables can't influence results generated by a control group. After changing certain dependent variables before each count, you can compare each outcome to that generated by the control group to gauge which method counted items most reliably. In this process, independent variables are a sample's size and source, while dependent variables are factors that you can alter between tests, such as counting techniques.
To carry out this counting method, you may use either a positive or negative control group. A positive control group aims to show that a counting method delivers positive results, such as reliable sampling. If your results confound this prediction, it's clear that this counting method relies on inaccurate assumptions. Conversely, a negative control group aims to prove whether a counting method delivers negative results, such as selecting unrepresentative samples.
Location-based sampling involves dividing an organisation's goods into groups based on their location within its warehouses. You may then count the type, number and financial value of a single group's items each day, before excluding the group and shifting focus to another. Depending on the scale of a firm's operations, this process may take place over a period of days, weeks or months. At this process' end, you might compile each location's results onto a single inventory database, before recommencing the counting process.
To ensure that the process offers accurate results, you can draft controls to prevent colleagues from moving items between locations during a count. You could then avoid either overlooking existing stock or counting it multiple times.
Item-based counting involves splitting items into groups based on their productive purpose to make it easier to judge which items to reorder from suppliers. In this context, you may review the organisation's stock data, before asking junior colleagues to visit each location recorded as containing a certain good. You can then use colleagues' findings to either verify or amend these records. By using this method, you could more accurately calculate inventory levels as warehouse colleagues count each example of this item in a single shift.
The section below provides contextual examples to explain how counting methods may work in practice:
Mr Stephenson works as an inventory manager for EVehicles Ltd., a UK-based electric vehicle manufacturer. In this role, he's responsible for overseeing regular stock counts to determine if the firm possesses enough resources to sustain production. In the past three months, supplier sales prices of electric motors increased by 20% due to rising inflation. To gauge if the firm had enough stockpiled motors to cover short-term output without reordering supplies, Mr Stephenson commissioned an item-based counting process.
To implement this process, Mr Stephenson asked 10 junior warehouse colleagues to count such items, using past records to determine their likely locations. Comparing recent output to three-month-old stock records, he determined that the firm may own about 3,500 electric motors. However, after completing this count, his colleagues stated that only 2,300 motors existed in these locations. In response, Mr Stephenson asked his procurement colleagues to order 1,200 motors to cover this shortfall.
Ms Robinson works as an inventory manager for CreativeCrafts Ltd., an arts and crafts products producer. To judge the firm's ability to fuel short-term production without reordering raw materials, she decided to review Warehouse A, which contains paint, glue and glitter supplies. According to the firm's most recent study, this warehouse contained 5,000 paint tubs, 3,000 glue tubs and 2,000 glitter tubes, respectively making up 50%, 30% and 20% of its items. To avoid biased results, Ms Robinson used the random sample counting method.
Over a two-day period, Ms Robinson asked 10 junior warehouse colleagues to randomly sample 1,000 items from the warehouse. At the end of this stage, her colleagues sampled 530 paint tubs, 170 glitter tubes and 300 glue tubs, respectively making up 53%, 17% and 30% of the sample group. As these percentages broadly matched the previous study's results, Ms Robinson was confident about their accuracy. She then eliminated these items from her study, before asking her colleagues to repeat the process by randomly selecting 1,000 more items.
Mr Patel works as an inventory manager for SmartTech UK., the UK subsidiary of an international electronics producer. In the UK, the firm has three main production lines: a premium smartphone, a budget smartphone and a smartwatch. The premium smartphone costs £750 and generates 15% of annual sales, while the budget model costs £220 but generates 80% of annual sales. The smartwatch costs £300 and generates 5% of yearly sales.
Given the budget model's market strength, Mr Patel commissions fortnightly counts to judge if SmartTech UK has sufficient inventory to meet short-term demand. For the premium smartphone, he commissions monthly counts, while for the smartwatch he commissions twice-yearly counts.
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