The importance of Bill of Labour within PLM
Most (if not all) PLM systems evangelise the need for detail and accuracy when compiling Bill of Material (BOM), but few pay more than scant regard to Bill of Labour (BOL). Whilst all PLM solutions available today have the capability to handle Bill of Labour, all rely equally on data which is either simply keyed in by the user or extracted from third party software – regardless of data accuracy, consistency, origin or integrity.
All too often, the BOL within any given PLM system is populated with data that is either historical or estimated. This leads to inaccuracy in Product Costing and Production Planning, with the end result that products are either over or under costed and delivery dates are compromised – Without accurate and current data, from a trustworthy source, this leads to further increases in manufacturing cost through increased and excessive overtime (which is in direct contravention of most Social Compliance guidelines) and to higher transport costs due to the need to use air freight to achieve on-time delivery. And in a “worse case” scenario, a supplier to a Retailer / Brand may sub-contract production to a third party where Social Compliance and product quality are severely compromised.
Taking this all too familiar scenario into consideration and if we accept that BOL is a vital part of the product development process (more on this in Part Two), then we can perhaps begin to see why it is essential that validated, consistent and accurate data should be used when compiling the BOL for any given product. One wouldn’t confirm an order based on “best guess” material costs so why do so many companies do so when it comes to labour?
Furthermore, the ideal scenario is to populate the BOL as early as possible within the product development process, which highlights the need for a tool which, in addition to being accurate, consistent and trustworthy, enables the end user to predict manufacturing time and cost to subsequently provide a consistent and standardised means of quantifying time, cost and product value
Why is the ability to predict time and cost within the product lifecycle so important? Well, let’s look at that from two different perspectives –. First of all, when designing and sourcing products, a Retailer / Brand must be able to “price point” such products to ensure that the customer perceives value whilst simultaneously safeguarding its own profits. AllRetail /Brand organisations will, however, source goods from multiple suppliers, with the supply chain spanning multiple geographic locations, multiple manufacturing sites and even multiple continents. In reality, the time and cost of manufacturing an identical product in multiple sites will always vary – this due to the wide variation of equipment, work aids and attachments, differing manufacturing environments, working methods, payment schemes and factory efficiencies.
The Retailer / Brand, however, needs to ensure that they price their products in accordance with market forces (price and perceived value) and yet has neither the ability to determine an exact product time and cost for each and every supplier in their supply chain nor the internal resource to administer and monitor multiple times and costs associated to that process. So, it becomes evident that a solution that predicts an accurate, consistent, achievable and reliable benchmark for both production time and cost is essential in pre-production cost discussion and negotiation.
Turning now to the second perspective, the manufacturers in the supply chain need to predict manufacturing time and cost if they are to protect profit margins and ensure on-time delivery of the required quantity on a given date. Without that ability the manufacturer risks a) losing the order by “guesstimating” too high a price or b) compromising profit margins by offering too low a price and/or having to commit to excessive overtime and/or by incurring otherwise avoidable air freight costs. Or even worse, sub-contracting production to a third party and losing control of Social Compliance and product quality.
So, it is evident that both ends of the supply chain benefit when accurate, consistent and predictive data is available to populate the BOL at product inception. Moreover, if that data comes from the same consistent and standardised source, any “dispute” can be resolved through reasoned discussion and comparison of like-for-like technical data, leading to what we refer to as “fact based negotiation”. With accurate, consistent and trustworthy datain place at an early stage in the product development process, both buyer and supplier can avoid the traditional stance of “horse trading” and haggling over price –a process itself based on nothing more concrete than personal experience, guesswork and price pressure!
In short, a reliably populated BOL removes uncertainty when developing new products and, as we will see in the second instalment of this series, is a critical element in remaining profitable and competitive in today’s increasingly challenging markets.