You are a major manufacturer of medical diagnostic reagents. You make most yourself, but you have subcontracted manufacture of a minority of products to a supplier who has the necessary biochemistry knowledge. The contract includes materials and labor and the price is set at a ‘Per Item’ rate with quantity at your discretion. After 5 years the contract is up for renewal and you contact the subcontractor to confirm the price. You are enraged when the subcontractor insists on a 40% price rise across the board. You have no other source for the material which Marketing insists is essential to the business as a whole. Do you agree to the price rise or come up with another approach?

What Arguments Do You Have?

Your search for clues: the existing contract states that the supplier must provide evidence of cost increases. They have not provided any, and do not appear to have a method for linking expenses to sales price outside standard cost accounting, the details of which they are reluctant to reveal because it contains information that is proprietary.

Use of 3rd Party

A 3rd party can always help in a stalemate. You know one who has a method for evaluating manufacturing costs that can be done in just a few days at site. The method does not need to know about parts of the factory that deal with other products. The method is particularly applicable to batch manufacturing processes where batch related costs, such as QC testing are disproportionate to those that vary strictly with volume such as packaging materials. You will then see what is making costs vary and the supplier will obtain justification for its claims, in a way that conventional cost accounting does not do. They agree to allow a factory visit, provide the necessary information and will accept the analysis if it totals their own estimate.

What the Analysis Reveals

1. The marginal cost of manufacture of each component is relatively small

2. At current prices some of the products are not profitable and some are very much so

3. Changes in volumes required over the next 5 years will significantly change the unit manufacturing cost

4. The supplier has limited ability to reduce cost by increasing productivity

5. Batch size is the major driver of unit cost

The Negotiations

You inform the supplier what you think their Gross Margin will be as volumes change. The supplier responds by saying that this is not enough. Cross-examination reveals that they worry about material cost inflation, labor cost inflation and that the actual volumes may fall short of your forecast. You add features to your ‘model’ of their operation to account for the inflation effects. You agree what these should be. Since Gross Margin is the criterion that the supplier insists on using, you discuss a minimum and maximum for this. You agree that prices should be set so that they are capped when the calculated margin reaches the maximum and boosted when the margin drops below the minimum. The key agreement is to use your cost model to perform the calculations.

The Result

The cost model ‘calculator’ is part of the legal contract. By re-assuring the supplier that the real risks they face are built into the price, they agree to a lower Gross Margin, which amounts to a price rise much less than originally asked for. Your saving amounts to millions of dollars and you restore the relationship to one of mutual respect.

When developing a new product or service many business advisors encourage businesses to undertake market research, and rightly so. Traditional market research work can study different market segments, highlight the size of the market, who the competitors are (and what they are doing) and even future trends for the market. Business advisors will also encourage businesses to undertake a SWOT analysis (strengths, weaknesses, opportunities and threats) to help with strategic planning and encourage them to conduct a study into the protection of their new ideas via patenting. However that is often where it stops. If it looks as if there is a market big enough to make a profitable product, the product is unique in the market and the product can be protected (via patenting or some other means) then businesses are commonly encouraged to dive into the expensive product development phase. After all, time to market is important.
Often, too little attention is given to whether the product actually has a useful purpose, whether the product would be easy to use and whether the product would be appealing to the target customer. Businesses, business advisors and even investors are sometimes guilty of glossing over these issues and relying on a hunch without conducting the necessary research. Businesses who dive into the product development phase straight after conducting market research are taking a very high risk strategy. It seems much more sensible to study whether the new product idea meets the needs of the target customers first, by conducting some initial customer research. Not just to ask customers what they want or if they like the new product idea or not, but to see if the new product could really add value.
Early customer research work can help clarify key product design and product positioning issues that must be right to give the new product a better chance of success in the market. One customer research method widely used in industry today to gain customer insight is called ethnographic research. Ethnography is the study of people’s everyday lives. Ethnography goes beyond questionnaires and focus groups and uses participant observation and interviews to capture and describe customer behaviour, beliefs and values. Ethnography can be used to uncover discrepancies between what people say they do and what they actually do; to identify needs that people can’t articulate explicitly; and to describe how products and services are used and the meaning people attached to them. Please check out some of my previous articles as well as the Light Minds website and links to learn more about the use of ethnography in new product development.
My personal experiences are that far too much money is wasted unnecessarily in new product development because businesses have rushed into the product development phase straight after the market research stage. Finding and fixing problems once detailed prototypes have been made, or even after the new product has been launched on the market is a very expensive way to run a business. Early customer research can help avoid some of these problems and can help put in place a clear product design and marketing plan.

Statistics on the success rates of new products show that for every four new products that enter development, only one becomes a commercial success. In the UK, at least 50% of new products fail within their launch year. The healthcare sector is particularly challenging.

Previously I described the importance of meeting a customer need and the benefits of using ethnographic research to discover new product opportunities or to evaluate existing products. But you still need to translate these insights into product solutions.

There are three very simple but key elements that you must consider when designing your new product solution.

Firstly, your new product must have a clear useful purpose and address a need from patients, carers or administrative staff. This purpose can be derived using the ethnographic research approach described previously. If your product does not have a clear and useful purpose that meets a need you are going to struggle.

Secondly, the use experience of your new product must meet or surpass expectations. It is not good enough just to have a clear use for the product. The design of the product must to be easy to learn and use.

Thirdly, your product must be desirable and appropriate. This affects not just the physical design of the product but everything associated with the product from packaging to marketing.

When you are creating and designing a new product you must consider the use of the product (what does the product do), the level of usability of the product (how does it work, can it be used comfortably) and the meaning that the product conveys. Meaning refers to its aesthetics, cultural messages, inherent symbolism and the metaphors it incorporates. Well-designed products consider both function (use and usability) and meaning as both affect a person’s total perception of the product. “Often the product’s meaning is most influential in the customer’s purchase decision and in the creation of a positive ownership and use experience”, (Sara Beckman & Johannes Hoech, Harvard Business Review, 2000).

However every product that you create should also have a consistency with regard use, usability and meaning covering product development, design, manufacturing, marketing, branding, advertising, packaging, etc. You cannot create a meaning of quality and elegance through design, packaging and advertising if the product’s use and usability are not of equal quality and elegance. As Michael Barry (an inventor of many successful products) puts it, “a successful product is the physical embodiment of a strategy that aligns users, technology and culture”.

When you are creating and designing your new product, take a step back for a moment and ask yourself about its use, usability and meaning. I think you will find it a useful exercise. All elements have to be spot on in order to create a successful product solution. The next article in the series will comment further on the power of prototyping, role play and product testing and how they can be used to study the use, usability and meaning of your new product.

We all know that forecasts are always wrong.  So why do we make them, then?

Here’s a story about some decisions made in 1992 still relevant 13 years later, based on forecasts made then.

The question was “What freeze drying facilities should be provided to cater for lyophilization demand over the next decade?”

It’s always best to be flexible about plans for the future. Business changes, new products come and old ones go. If you are lucky, you can cope with most capacity requirements by hiring more people, working more shifts, renting some offices or using simple easily reproduced manufacturing processes. However, the chances are that you have got some processes that require large capital expenditure, take a long time to put into place and can’t easily be changed once you’ve built them.

Lyophilization is one such process. Great for ensuring long term stability and activity of reagents of biological origin, but requiring special equipment, elaborate validation and special facilities. So, when you are planning lyophilization facilities for product lines lasting more than a decade, you face some severe forecast challenges that boil down to “how many and what size should the lyophilizers be?”  Errors in judgment can easily result in running out of capacity too soon, requiring additional capital expense, not to mention a probable space problem (where do we put it?), along with having to rush an unrushable validation program.

Alternatively, you will have to justify surplus capacity “just in case” under the spotlight of the annual budgeting round.

A forecast is needed of the likely products and batch sizes, of course. What is needed more, though, is a recommendation that is least sensitive to this forecast being wrong.
Here’s an example. The author was asked to answer this question in 1992. In a new facility, how many and what size lyophilizers are needed? For the needs of the next 13 years!

There are a range of variables: 

• A new range of products under development
• Unknown new components to be lyophilized
• Volume growth or decline in each
• Batch sizes dependent on shelf life and demand
• Unknown marketing initiatives in the future
• Changes in lyophilization cycle time
• Regulatory rules as to what can and can’t be lyophilised together
• Existing components still in design that might or might not need lyophilizing

Forecasts produced a chart for total lyophilization volume as follows:

Fig 1

With the minimum forecast volume 20% of the maximum, there was at least a conviction that zero was not an option!   The business had faith in its long term future.

So, what were the options?

The latter options were tested first: avoiding capital expenditure is always welcomed at board approval level. However, it was impossible for R&D or marketing groups to imagine a future where nothing was lyophilised, even if as a contingency. Experience with the biological components used in this industry had to rule here.  Subcontractors were sought out.  However, even those that could possibly have helped in the short to medium term could not be relied upon to provide long-term security of supply. Here was a strategic process that needed to be kept in-house in order to maintain that security. The subcontractor option was ruled out, at least for the “most probable” forecast.

Now the original question had to be answered: How many and what size should the lyophilisers be?

The forecast had produced an aggregate volume from a listing of current and projected components.  What it did not do was to clearly identify what batch size each would be made at.  This is crucial. If you want to lyophilise 20,000 vials a year, you could do it with different sizes of lyophiliser as follows:

• 20,000 vial capacity and do the task once a year, using approx 1/360 of its capacity with a drying cycle around 1 day.
• 5,000 vial capacity and make 4 batches in a year, using 1/90 of its capacity
• 60,000 vial capacity and lyophilise 3 different concentrations in the same cycle [if the product was supplied that way]

This provides many options.  What if product performance, at some time in the future, requires that a component must be made 4 times a year [perhaps its shelf-life has to be reduced, for example]? If you had specified the 5,000 vial capacity machine, then this would make no difference.  If you had specified the 20,000 vial machine, then you would still have to use it 4 times a year, but each time only filling it ¼ full.  Its capacity utilisation would be the same as the smaller one.  In this situation, why buy the larger one?

Multiply these contingencies by the full product projected product range, and you can see that building large to provide vial capacity does not necessarily provide capacity that can be used. At the other extreme, if you build too small, you will be able to use the capacity better, but at a price.  Sometimes you will have to make batches smaller than you really want in order to fit the lyophiliser space.  Making more batches to do this will incur the batch related expenses of doing so, e.g. more formulations, more QC testing.

So, how best to resolve this?

Using a spreadsheet to calculate the required number of batches across all the predicted products, the effect of lyophiliser size on the number required can be seen (Fig 2).

 
Fig 2

The exercise can be repeated with maximum and minimum estimates to give a spread. The number and size can be chosen to cover the worst case, without providing an excess.

In this case study, this was sufficient to make the choice and demonstrate its worth.
If necessary, the analysis can be extended to include balancing the capital cost of larger lyophilisers against the extra revenue expense of making and testing the additional batches that the smaller one will demand.

What Actually Happened?

After 13 years, the actual volume was within the forecast band.  During that period, volume had dropped off dramatically, whilst at the end it was on an upward trend.  Other completely unpredicted things happened too. New components were introduced (as had been expected), but these were only needed in very small quantities. The effect was to demand many more lyophilisation cycles, but each one only containing a small quantity.  With hindsight, these components could easily have been dried using a much smaller lyophiliser instead.  However, the machines were built and installed and once there could be used for anything. Such has been the case.  Capacity to still sufficient to meet current demand, and is certainly not too much.  The forecast has worked out right!

Now What?

At time of writing, the existing facility will be needed for several more years, but then may be replaced.  The 1993 question has been asked again.  It has been answered in the same way.

How do multi-nationals decide where to make new products? In this case, the choice was between existing facilities in the USA or the UK.  Each existing site made a product similar to the new one. Each had an established technology that would be used at the chosen site. The company also had a long-standing strategy to rationalize facilities in the two countries.

There was a prima facie case for the US site. It was local to the market for the new product, the time to obtain regulatory compliance was shorter and the current unit manufacturing cost of the existing product range was 20% lower.

Other considerations favoured the UK site.  Activity based analysis of the existing product lines in the two countries showed that marginal costs were much lower in the UK.   The UK used a process technology that was more modern and inherently more flexible.  Further, the existing US product was in decline, whilst the UK made one was still growing fast.  Capital plans for expansion could accommodate the new product without excessive new expenditure.  On top of this were financial advantages from tax benefits and local grant-aid.

The process of reaching the decision was effectively a competition by each site to bid for the new product.  Costs, inventory, responsiveness and capacity for both current and predicted new operations were presented.  This levelled the “fact” playing field. Each party had to assimilate the knowledge of the other over a range of issues such as regulatory matters, process reliability and operational efficiency.

They then had to commit to improvements to come up to the performance of the other. This commitment was more important that the final decision.

The example product was made in a single factory and shipped worldwide through a number of distributors to supply a market with a steady daily demand.  In other words, the true demand was completely flat.  The stock and ordering policy of the distributors adds variation which is reflected in variation of the factory’s output.  At the start of the period shown in Fig 3, the manufacturing response time was 18 weeks which coincides with the time between peaks of supply.  It can also be seen that the supply quantity varied by +/- 30% representing quite a strain on factory management (feast and famine).  Batches of the same product were made every 6 weeks and manufacturing lead time was 12 weeks for some of the components.

Fig 3

During the middle of this period, the factory was changed so that lead time for the most-awaited component was reduced to 8 weeks and batches made for shipment every 3 weeks. The right part of the graph shows that the peak to peak time reduced to 11 weeks (the new response time) and the amount of variation reduced to +/- 15%.  In this new regime, everyone was much happier and felt more in control.  A fringe benefit (actually probably ultimately worth more in Sales) was that the customers received fresher product and could keep it for longer before it reached the end of its shelf-life.

A further observation is that the reduced variation did not happen as part of a conscious effort on anybody’s part. It seems that the distributors “sensed” the greater responsiveness of the factory and adjusted their ordering and stock policy unconsciously.  In other words, it is human psychology that puts the variation into the demand (“I don’t trust the factory to deliver when they say, so I will order a bit more, in case”.  Followed a few months later by “I seem to have far too much, I’d better cut back drastically on my orders”). Greater responsiveness leads to greater trust and a more realistic ordering pattern.

Fig 4

It is worth also mentioning that manufacturing cost was held neutral, whilst inventory came down.  The chart shows on the same timescale how the inventory level of 3 of the components reduced as implementation progressed.

Definition
Response Time = Batch Interval + Process Time

An Analogy
It is helpful to think of it by analogy.  If you were planning to fly from A to B, how long should you allow to be sure of getting there?
 

Fig 1

i.e. Allowed Time = Interval between flights + Flight Time
 which equals 1 + 2 = 3 hours in this example.
If you arrive just in time to catch a flight, it will take you 2 hours, but if you just miss one, it will take 3.  In the absence of a flight timetable, you will need to allow 3 hours to be sure.
It is possible to talk about the response time for intermediate components too. However, it only makes sense if the intermediate is stocked: “planes must land at the airport”
 

Ways of Reducing It
It is clear from the definition that response time is reduced by:
• Making batches more frequently (reducing batch size)
• Reducing process lead time
However, the most common form of response time reduction is by the use of stocking points, in particular, finished goods.  Sales can then be in units (=batch size) of 1 and processing time is typically just the shipping time from distributor to customer.
Of course, buffering against sudden changes in demand by adding raw material, intermediate or finished goods reduces response time at the expense of inventory. So response time reduction should not be viewed as an end in itself. It needs to be done without increasing inventory or cost to be a credible improvement to the business.

Fig 2

A response time can be calculated for each set of processes which end in a buffer stock. The complete supply chain is thus an assembly of such links each with its own response time.
 
Thus there is generally more than one figure to be looked at, although the final one (nearest to the end customer) is the one most often scrutinized.

The Result
A more responsive factory:

• Is less likely to default on customer orders
• Has fewer disruptive changes to production plans
• Is in less of a panic

Fit with Management Strategies
Whilst not stated explicitly, Response Time reduction is the goal of many manufacturing strategies such as “Lean Manufacturing”.  However, there is nothing new about it as a concept.  Henry Ford can be thought of as an early advocate when he established a car production system that smelted 1500 tons of steel a day to turn out a car every 49 seconds in the shortest possible elapsed time.

It is a common sense concept. If you want to satisfy the customer, you must respond to their demands.

By James La Trobe-Bateman, reMODEL Consultants International Ltd

You have probably heard many times that products must meet a customer need to be successful. However if you are in the situation where you are developing a new product in the healthcare industry, how do go about discovering whether your product will meet the needs of patients, carers and key decision makers? This can be a difficult task, as quite often, they cannot tell you what they want. And if they can, that still might not lead to the creation of a successful new product. Research by Professor Clayton Christensen from the Harvard Business School finds that leading companies who have followed what their customers say have lost out to new innovations from other companies. This he has called “The Innovators Dilemma”. If this is true then maybe the traditional way of conducting market research is not adequate in the quest for discovering unmet customer needs and creating new disruptive product opportunities. What people say they want (and do) should not be the only deciding factor in creating new disruptive product innovations. So what are the alternatives? A new approach starting to become more widespread in industry is to conduct in-depth customer research and to treat potential customers as participants in the new product development process. In simple terms the approach is to

• Listen to what potential customers have to say.
• Observe what they currently do.
• Observe what they currently use.

In formal terms, this approach of in-depth customer research is known as ethnographic research and is defined as “the description and study of human culture”. It originates from anthropology where anthropologists spend significant periods of time with people from a specific cultural group and make detailed observations of their practices. Cultural groups could be tribes in the Amazon rainforest, teenagers, hospital patients, organizations and so on. In the area of new product development the customer research is conducted in a much shorter time scale to fit the needs of industry and is known as applied ethnography or rapid ethnographic research. However the research is still conducted in-context and takes place where people live and work, for example in homes, offices, hospitals etc. The power of taking such an approach is that it provides real life accounts of customers’ everyday activities, their behaviours, beliefs and values and highlights the differences between what people do and what they say they do. As a result needs are found that have not been directly expressed. Companies including Microsoft, Ericsson, IDEO, PDD, Light Minds and Kimberley Clark are using this approach to discover new product opportunities and also to evaluate products that are in the development stage. For example, Intel used ethnography to help develop some of the Allscripts Healthcare Solutions (www.allscripts.com). Bath University used ethnographic research to help design new information systems for the waiting rooms of Hospital emergency departments. It is also interesting to note that most of the new product ideas for the healthcare industry in the UK are coming from clinicians. I suggest this is because they are using ethnographic research techniques routinely (knowingly or not) as part of their everyday work. Once you have identified unmet needs of potential customers the next challenge is to make sure you translate these findings into a successful new product solution.