Lower Inventories as a Tool for Better Customer Service

There is an old adage that you can always buy better service by increasing your inventory level.  While generally true (having more safety stock will guard against supply chain “oops” or market variations), this generally equates to employing more working capital and as such goes in the wrong direction for today’s financially leveraged firms.

How then can lowering your inventory levels improve customer service?

Let’s look at how inventory levels are determined for stock items…

Inventory for a given item is dependent on several factors:

1. Lead time to replace stock
2. Shelf life/expiration date
3. Market variability ( seasonal, unpredictable, highly regular?)
4. Supply chain failure rate
5. Cost of the individual item to manufacture (inventory value)
6. Cost of stock-outs in lost market-share, income, reputation

Many companies depend on a calculated algorithm based on the above factors to send the “make” signal when new stock must be ordered.  How then can less stock be helpful?

Lowering stock levels is akin to watching the tide go out in the harbor.  As the water level drops, rocks start to appear.  What appeared to be a smooth surface on top of the water now reveals obstacles which had been hidden.  These are the issues which have been covered for by excess inventory.

With lower stock levels, the number of service level “misses” in the supply chain process will become more pronounced.  Yes, there will be a bit of (short-term!) pain.  These “misses” need to be categorized according to the service level model used.  By classifying the “misses” in a Pareto-type chart (looking at individual or grouping similar products or processes together), the areas which need improvement become more apparent. Now the work to improve begins.

Removing the rocks takes a bit of effort.  Improving the processes which led to the greatest amount of misses can form the bases of Lean initiatives, 6 Sigma projects, or purely scientific lab processes.  Once the cause is removed, the process is thereby made more predictable, shorter or cheaper.  The safety stock which was needed to guard against each of these eventualities can be reduced.  Usually reaction time is also decreased, so the market has less time to stray from the predicted trend line. Inventory level falls at the same time customer service level rises.  And so you go on to the next lower product or process in the Pareto analysis and improve both service and bottom line.

Validation is Not Like Baseball!

Ninth in a continuing series on process improvement and product development.

 Drugs and diagnostics are products and processes covered under the guidelines issued by the FDA and similar bodies. The underlying philosophy is that these products are critical to health and well-being, and so should be manufactured and perform according to pre-established specifications.

 

One of the best predictors of reliable performance is having a reliable manufacturing process. Parameters are usually defined during the design and scale-up phases and production runs undertaken to produce commercial quantities according to the intended process sequence.

 

These new or altered processes must undergo a “Proof of the Pudding” – a validation of the intended methodology. The rule of thumb is that 3 successful batches are necessary to prove out the method. Any product made during these trials is held in abeyance until the validation study is completed, at which point passing material may eligible for commercial distribution.

 

In an ideal world, the first 3 batches run are all successful from both a method and product performance standpoint. Dream on!

 

In the real world, one or more of the validation batches fail. The list of potential root causes is enormous, ranging from flawed raw material quality specifications to equipment engineering parameters to interactive process variables conspiring in negative ways.

 

In many cases the flaw is identified, fixed and a new trial series tee’d up.

 

In other instances, the viewpoint is simply to explain away the cause for reasons of cost, time or convenience and tee up a batch without altering any fundamentals. The result is predictably unpredictable – the new batch may pass or fail – who knows in advance anyway?! This in turn leads to a sequence of validation batches which pass or fail until the magic total of 3 successful ones are arrived at and victory is declared.

 

Here the baseball analogy enters in.  A validation pass/fail sequence which looks like a long at-bat (Ball, strike, strike, ball, ball, strike 3 – you’re in!) may get you to the desired 3-strike result from the pitcher’s perspective, but the route taken doesn’t exactly inspire confidence if viewed from a potential patient’s perspective.

 

A validation is meant to prove control and reliability of the process. 3 successful batches may be a means to that end, but it is not the goal. Validation is not complete until control is demonstrated!

Climb Every Mountain?- Not!

 Eighth in a series of articles on process and product development.

Post-launch questions on new products often pop up from market sectors or changing applications which were not initially considered during the design phase. Technology-driven companies often rush to tweak a product to allow for each new application.  This may involve different protocols, new materials, or different specifications (both broader or narrower) for release.  In this rush to please, some larger issues need to be considered.

How big is the opportunity being addressed?  Some market opportunities may be truly worthwhile, having been either overlooked or newly generated.  However, markets can be minor or local, and not worth the additional investment of R&D effort, particularly when there are other more fruitful uses for the resources applied.

How will the new tweak affect the ease of production?  Is this twist something which will have no noticeable effect on the product, but cause higher failure rates, longer processing times, or drains on resources elsewhere?  Is the margin of safety been compromised or skinnied too much?  Has product stability been considered in sufficient depth?

Companies which are technology-driven (usually dominated by R&D)get enamoured with all the additional features and applications which they can add on.  This can delay other new products in the pipeline as well as make life unpleasant (fewer degrees of freedom) for the manufacturing arm, which usually dutifully follows along.

So the answer is:  Consider carefully the impact vs the resources and risks.  Not every problem is worth solving – some markets deserve to be left unserved to the benefit of larger opportunities!

Scale-Up – Is It Necessary?

Seventh in a series on process and product development tips.

 A normal step in the product development cycle is the scale-up of batch size.  This can occur at any of several stages:  The initial move up from bench or trial scale, the inauguration of larger capacity production equipment, or merely in response to increased market demand.  Each of these scenarios is subject to critical analysis, but each carries a different burden of justification.

The scale-up from bench trials typically involves initial onesy-twosy methodology which is extremely labor intensive for both production as well as quality control.  Equipment time per batch produced usually occupies a fixed interval, along with any testing protocols.  This leads to a relatively high unit cost in small batches, a cost that is normally not commercially viable from an ongoing production standpoint.  Hence the need to find a reasonable scale which can generate a positive and sustainable margin is a top priority before product launch.  The over- or under- sizing of development needs are frequently the product of poor market intelligence, resulting in a  large expired product scrap exposure or mad scrambles to satisfy market demand after the product is launched.

Newer, larger production equipment carries the promise of larger, more efficient, batch sizes and consequently lower unit costs.  This assumes a number of factors which too often are taken for granted:  The increased scale will perform similarly in the new production process (yes, new equipment will behave differently!) and the resulting product will have the same performance profile (failure rate equal or better than status quo).  What validation protocols are necessary to bring the unit on line?  How extensive a testing program, regulatory approval process, or other scarce resources (people, production time or materials) needs to be applied?  Is this justifiable?

Even the simple scale-up of an existing process in existing equipment is not necessarily a slam dunk.  Given the assumption that the duplication of existing process steps at scale factor X carries the same risk of failure as status quo, are the consequences of failure considered?  What is the batch cost?  Are the critical resources to be committed (material and personnel) available for a re-do within the time interval required, without jeopardizing market presence?  Does this require larger safety stock positions for raw materials?  What are the expected direct gains in the cost profile?  How does the demand pattern of the product compare to its expected batch size shelf life?  Validation batch needs usually are limited, but may tie up capital until all trial batches are released after final review.

The answers to any of the above generalized situations depend on individual company and product characteristics, both within and external to the firm.  Improved product cost versus other product opportunities in the portfolio may change the calculus, along with varying market and competitive conditions.  The bottom line should be improved on scale-up, but have you chosen the right ones to focus on first?

Is It Good Enough?

Sixth in a continuing series on product development and process improvement.

The race to get new products to market never ends.  Faster is more desireable, but is it better – maybe!

The usual priority in getting new products to market is fastest date to the shelf.  However, speed is always in dynamic tension with making the best product.  Best product can mean many things (highest assay, most features, best performance, most robust) all of which require more extensive customer input, design, testing.  In other words – more time or R&D effort!

Factors promoting speed can be classed as:

            1.  Sales to be gained (or not lost to a competitor) on an existing product.

            2.  Immediate need to meet a crisis or temporary market opportunity.

            3.  Maximize return on development process by minimizing necessary inputs.

            4.  Maximize protection of intellectual property (eg. patent life).

            5.  Availability of resources which can be diverted to the next project.

In contrast to this, a better product may address many other concerns:

            1.  Market share to be gained with improved or superior product.

            2.  New market to be opened up through innovation.

            3.  More robust platform, with fewer customer complaints or hand-holding.

How then to choose between the two?  Let’s look at the risks in the development cycle.

            1.  What is the cycle time to introduce a new generation?  This needs to include internal development as well as any external approvals.

            2.  What is the expected benefit from the improvements?  How does this stack up against expected incremental gain in sales or market share?

            3.  What is the expected cost of such additional development work? 

            4.  What is the product cost of such innovation?  Will it affect price or margin?

            5.  What is the cost of failure of the semi-developed (faster) product?  This needs to reflect at a minimum safety, efficacy and reliability, as well as possible legal costs.  The subsequent fallout on company reputation must be considered not only for this product.  The halo effect on other products may result in a cascade of longer regulatory examination times, lowered portfolio sales because of diminished overall reputation and longer time to acceptance in the market by opinion leaders.

The dynamic interaction of these considerations changes from product to product, circumstance to circumstance.  The desired course can also be affected by the company’s positioning in the market as an innovation leader, quality leader, or cost leader.  

The answer to this question is the product of management’s confidence in the development process, market intelligence, and overall direction.  Any answer may be right at a given point in the process and wrong later on.  Choose wisely!

A Project Too Far…

Fifth in a series of articles on product development and production optimisation.

Today’s product development environment is dominated by the need for speed.  Deadlines for market launch are ever shorter, and the pressures to minimize the time and experimentation have never been greater.  In the headlong rush to make these short timelines, are product developers making the right choices?  In many cases, the answer is no!

For a new product which is to be part of a portfolio with others very similar, the temptation to ride on previous products is extreme.  This is usually reflected in many assumptions at the planning or early development stages.  “This product will behave like the last one.”  This leads to cursory exploration in many areas (“old ground”) and overarching emphasis on the novel component(s) only.   The shortest, straightest, minimalist path is chosen. In order to make the aggressive launch date, “We don’t have time to do any more experiments!”  This can be successful, but only up to a certain point…when problems arise!

When problems arise at later stages and validation runs, developers are already mesmerized by the impending launch date, now only x months away!  The design has been locked in.  What has gone wrong?  How to fix it?  Usually no good options are considered, except to plow straight forward.  That is usually the crux of the problem!  Product parameters have been fixed, whether by design or confluence of other component needs. A crash program to find a workable solution is immediately started, with extra effort and manpower.  Eventually, sometimes an answer is found at the cost of performance or “make it fit” pressure.  The product is launched late or with cost overruns which significantly affect ROI.  If only developers had the tools and data to solve these issues at hand – but they don’t because they glossed over them in the quest for speed.

In the initial experimentation, the critical variables need to be defined for the system as a whole.  This can be done using factorial screening experiments.   A little extra work, perhaps – usually only one or two extra testing cycles are involved – a week or two additional time spent. The resultant analysis yields a table of variables, which ones matter, and the extent to which they interact with other.  The entire performance surface is defined for the normal operating range.  Having this knowledge in hand, one is equipped to face any later issues which arise in qualification runs.  With good information on the limits of the performance space, it is much easier to determine which component parameters are in good shape and which ones need to be fixed.  Interactions and other “gotchas!” are already known, partially defined, or designed out of the process.  The path to a workable solution is usually much more evident and will require less frantic thrashing about in search of potential culprits under time pressure.  Proper preparation of the basics will lead to a much smaller effort needed to find the solution under critical conditions.  Hence, an incremental effort at the beginning will actually lead to a faster launch than taking “short cuts”.

Interactive New Product Development

 Fourth in a continuing series of articles on product and manufacturing improvement tips.

Every company wants to expand its markets and grow revenues by introducing new and exciting products.  Most companies have more ideas than they can tackle, so projects stand in line until time, money, and staff become available.  All the more reason to do things right the first time!

The traditional model involves Marketing outlining a new product proposal, which is then taken by R&D.  The research phase may involve fundamentally new investigations, or begins from past practice and previous products.  R&D, by its nature will seek to come up with the best possible product – but wait, here is another improvement too, and another, and … 

 

When is the product ready to go to the next phase (usually Manufacturing, but it could be launched directly from R&D!)?  Was the initial product proposal sufficiently detailed in its specifications to determine which attributes the customer will pay for, and as such where to stop?

In the traditional model, the Manufacturing staff is now handed a thick dossier (“thrown over the wall”) and told “Now just go make this!” while R&D turns its attention to the next project, apart from some attendance at trial production runs.  Usually things do not go according to predictions, and time lines drag on and on.  Where is improvement possible? 

Firstly,  Marketing needs to know its markets extremely well in the sense of what product performance or attributes customers are satisfied or delighted with.  The product proposal needs to include hard minimums on specifications.  These specifications need to be vetted by R&D as possible, and just as much by Manufacturing, who has best awareness of current or anticipated manufacturing capability.

Secondly, as R&D begins its investigations, it should have up to date knowledge of the manufacturing possibilities and limitations.  This may involve rates in units or equipment capacity, shift work, best practices and any innovations brought to the factory floor by Manufacturing or seemingly unrelated R&D projects( eg from other divisions).  The practical aspects of manufacturing are best shared on a day-to-day basis by manufacturing representation on the project team, not as later add-ins when design is complete.

Likewise, Manufacturing can share insights at the beginning of the design phase, so as to avoid developing an un-manufacturable or impractical product.  Small changes in development can often lead to huge improvements in manufacturing economies and productivity without affecting product quality or performance in the negative sense.  Examples are unnecessarily tight (or loose) specifications for individual steps based on experiments done or needed to be done.

This interaction of R&D with Manufacturing usually leads to smooth production trials, since many of the issues have been identified and dealt with beforehand.  Since Manufacturing is not learning the basics of the product only during trials, the “oops!” factor is minimized and failed trials become a rarity.