Archive for December, 2010

Top ten reasons your holiday gift will arrive late…

Published December 23rd, 2010 by Lori Smith 0 Comments

From everyone at Kinaxis, we wish you a happy holiday season and all the best in 2011!

It wouldn’t be like us to wish you a happy holiday without including some supply chain humor, so from the Late Late Supply Chain Show, here are the…

Top Ten Reasons Your Holiday Gift Will Arrive Late:

10.  Santa made a tactical error in choosing a “fly by night” 3PL instead of his usual crew of reindeer.

  9.  Santa refused to go through the body scanner and the TSA is still patting him down (he’s a big guy you know…)

  8.  Santa outsourced to China and lead-times have ballooned – it’ll be a ‘Christmas in July’ scenario for many!

  7.  Global warming has advanced to the point that the North Pole melted.

  6.  Pixie dust is on allocation.

  5.  The fireplace in Santa’s North Pole residence was mistakenly filled with Kindles instead of kindling.

  4.  Santa’s visibility only extends to the bottom of his eggnog glass.

  3.  Santa bought SAP…and is still implementing.

  2.  The “naughty” and “nice” data fell into an Excel abyss. Guess which list you ended up on?

  1.   Santa told key members of his manufacturing team, “Go elf yourself.”

For more supply chain humor, and to join in dynamic supply chain discussions with nearly 4,000 professionals, visit the Supply Chain Expert Community

Posted in Miscellanea

The supply chain disruptions you’ll never plan for

Published December 22nd, 2010 by Carol McIntosh 1 Comment

The eruption of Iceland’s Eyjafjallajokull volcano last spring was fascinating for a number of reasons. For example, photos of lightning inside the plume of volcanic ash, such as these seen at National Geographic’s website, are mesmerizing.

More importantly, the ash cloud itself presented significant business ramifications for companies around the world. I believe we will study the volcano’s eruption—and, consequently, the disruptions to supply chains around the world—for years to come because the impact was both so widespread and pronounced.

A recent BusinessWeek article described how automotive manufacturer Nissan Motorwas forced to shut down three auto assembly lines in Japan because the factories ran out of tire-pressure sensors when a plane carrying a shipment from a supplier in Ireland was grounded.

I’ll wager that you expect disruptions from hurricanes and possibly tropical storms, and maybe even a blizzard across the Great Plains. Since those events are likely, it’s smart to create contingency plans that account for alternate transportation routes or even modes. Furthermore, you may even have contracts in place with suppliers for alternate parts, and perhaps even contracts with alternate suppliers for necessary parts or components. But sometimes an unexpected event—like a volcano eruption—disrupts the supply chain. The question then becomes: How will your company respond to this unanticipated event?

Obviously, the first challenge is to realize that an event of some type has occurred or is about to occur. But even more significant, is the response. How quickly your company responds and just what that response is, may have substantial impact on the company’s performance and, possibly, its bottom line.

That’s why it’s critical to have tools and processes in place to respond quickly to unanticipated events that aren’t covered by a mitigation strategy.

  • These tools must deliver visibility across the supply chain and provide alerts when an event is imminent, they must also include analytics so users can understand the importance of the event and the impact it will have.
  • Secondly, the tools must allow users to collaboratively simulate possible solutions, such as splitting orders, expediting orders and finding alternate sources.
  • The next capability may well be the most important. Once simulations are created, they must be compared and contrasted to determine which one best meets corporate goals and objectives. Using a multi-scenario scorecard allows users to compare the possible solutions and measure the impact of each potential resolution on key corporate metrics.

Consider these two possible solutions to a critical parts shortage….

The first solution is to use existing inventory and split apart orders. Customers will not receive their full order, but they will at least receive part of it. A second possible solution is to expedite shipment of parts from an alternate supplier to your facilities, fill the orders, and then expedite shipment to your customers.

The first possible solution results in a decrease in on-time delivery and, potentially, a decrease in revenue for the quarter. The second, however, will result in an increase in cost of goods sold and a corresponding decrease in margin.  How do you know which route to take?  These results, compared against a given target and appropriately weighted, provide an overall score for each solution. Thus, an analyst can then use those scores to determine which scenario best suits corporate objectives.   How you make those quick decisions and how well they align with corporate objectives can make or break a company’s bottom line.

Let me know what you think; either about responding to unanticipated supply chain events or photos of lightning in clouds of volcanic ash.

Posted in Response Management, Supply chain risk management

The benefits of attribute based forecast generation

Published December 20th, 2010 by Martin Buckley 0 Comments

Attribute based forecast generation can be defined as using the common attributes of a particular group of products to more accurately forecast future demand at the individual SKU level. Forecasting is part science and part art, so the more we can move the analysis to the science side, the better we are able to develop a process driven forecasting model not based on an individual’s ‘gut’ feel. This is an important requirement when managing a large number of SKUs in a complex, competitive marketplace.

The benefits of increased forecast accuracy include:

  • Increased customer satisfaction due to reduced stock outs
  • Reduced write-off and obsolescence costs due to unsold inventory
  • Lower inventory carrying costs, as less buffer stock is required to cover missed forecasts

Significant benefits can be realized in a company’s top and bottom line results if a more accurate forecast generation process can be realized. One of the cardinal rules of forecasting is that a forecast becomes more inaccurate as it goes further out in time. Another is that a forecast becomes more inaccurate as the granularity is increased (ie. It is easier to get an accurate forecast at the business unit revenue level than it is to forecast the number of units of each SKU that make up the sales for that business unit).

This second rule can be better addressed by focusing not an individual SKUs sales history or possible future trends, but by looking at the ‘group’ this SKU(s) fall into and analyzing its history and trends. The attributes shared by these SKUs constitute their forecast group. The advantage of grouping forecast SKUs are many:

  • A lot of market research is available at a higher level in the marketplace (at the channel product category level versus an SKU level). Market share analysis must be done at this level
  • Aggregating SKUs reduces the month to month demand fluctuations seen at the SKU level, allowing for better data analysis for trend forecasting (reduces the noise)
  • Revenue forecasting generally occurs at the product group level or higher. Since revenue projections are the most common driver of forecast models, a better alignment between forecasts at the SKU level and revenue forecasts can be achieved if there is a clearly understood link between the two
  • A better alignment of revenue and SKU forecasts allows the business to more clearly drive production (also known as the sales versus production forecast). A poor alignment between the two can lead to missed sales numbers, increased inventory carrying costs, or stock outs.

The breakdown of the revenue forecast into a realistic SKU level forecast can be complex, and can vary greatly among different business units and markets. While these different processes can lead to a more accurate forecast based on local market conditions, it makes it very difficult to get a true picture of the alignment between the global revenue forecast and the individual unit forecasts, as the methods to get from one to the other can vary greatly.

This leads us to the recognition for the need of a formal, structured process for generating SKU unit forecasts from revenue forecasts that can generate a better forecast for the business as a whole. In order to allow the process to accommodate the differences between markets and regions, it must be have the functionality to allow for market specific processes, while maintaining a common underlying process that can tie back to the revenue forecast. The best way to achieve this goal is to use region and market independent product attributes, as they can ‘filter out’ the variations that can occur due to different business cultures. This also describes the best product attributes to select, as they should reinforce the underlying commonality of the SKUs being forecast. Market specific processes can then be applied to fine tune the forecast for a specific market or region.

In order to more accurately predict future demand at the SKU level, a tool is required can process large amounts of historical data and knowledge based assumptions quickly. This allows the analysts to perform what if simulations and determine the effects of various assumptions, as well as incorporate any trends that are evident in the marketplace. This leads to another “must have” feature: the ability for the analyst to easily and quickly incorporate trend simulations into the numbers. By using aggregated attributes on multiple levels and presenting the numbers in a percentage of total view, the analyst can quickly modify the splits at each attribute level to reflect known assumptions or model future trends, while keeping the totals within the revenue guidelines (the sum of the percentages must always equal 100). As well, by modifying percentages versus actual numbers at the lower attribute level, the overall revenue forecast can be kept consistent throughout the forecast process. The revised percentage splits can then be applied to the revenue numbers to break them down into a SKU level forecast that ties back to the revenue in an understandable way.

In summary, it is desirable to have a close correlation between the revenue forecast and the SKU level forecast. The best way to get there is to use product attributes, historical patterns, and the analyst’s expert knowledge to break the revenue forecast down to an accurate SKU level forecast. A tool that can support an underlying, formalized process with enough flexibility to allow for regional and market differences will deliver the optimum solution.  This tool must be intuitive to use and allow the analyst to quickly generate a valid forecast that supports the consensus revenue projections.

Posted in Inventory management, Sales and operations planning (S&OP), Supply chain management

Do you trust yourself to collaborate? The real barrier to collaboration is not technology, but trust

Published December 17th, 2010 by Trevor Miles @milesahead 2 Comments

 When I need inspiration I normally go to TED.  I can normally find a topic that is peripheral but pertinent.  Such was my quest with “collaboration”.  I believe very strongly in the value that collaboration can bring to massively outsourced supply chains such as we see in electronics and apparel.  But what is collaboration and what value does it bring?  All too often what we see as progress in collaboration is an exchange of data, perhaps on a more frequent basis, using EDI, when really collaboration is about working together to achieve a shared objective, but perhaps not a common goal.  By that I mean each party is playing a part (their individual goal) in reaching the shared objective. Watching two fascinating talks on TED titled “Deborah Gordon digs ants” and “Howard Rheingold on collaboration” helped me to frame this discussion.  Ants do indeed exchange “data” with each other, but somehow they are able to determine which task to perform that is in the best interest of the colony, changing their roles on an as-needed basis. People went from hunting rabbits through individual action to hunting mastodons through collective action. In other words, collaboration is a lot more than exchanging data using EDI.  Or is it?  A search of the internet brings up the following definition for “collaborate”:

col•lab•o•rate   (k -l b  -r t )

intr.v. col•lab•o•rat•ed, col•lab•o•rat•ing, col•lab•o•rates
1. To work together, especially in a joint intellectual effort.
2. To cooperate treasonably, as with an enemy occupation force in one’s country.

I think this definition brings together the ying and yang of collaboration very neatly.  On the one hand we see collaboration as something positive that will bring mutual value.  On the other hand we view collaboration as working with the enemy to the detriment of our own group.  What I find fascinating is that the same action can be perceived to fall in either category depending on the perceived objective and the level of trust one has of the party with which one is collaborating.  The conclusion I came to is that the real barrier to collaboration is not technology, but trust.

This came out loud and clear in a recent discussion titled “What’s happened to CPFR” in the Institute of Business Forecasting (IBF) group on LinkedIn (membership required) that was started by a guest blog by Lora Cecere of the same title on IBF.  For those who may be unfamiliar with the term CPFR it is an abbreviation for Collaborative Planning, Forecasting, and Replenishment which starting in 1995 as a Wal-Mart initiative to improve the efficiency of planning and replenishment between retailers and suppliers.  Clearly collaboration is at the very heart of this initiative.   The VICS organization has been promoting CPFR for a number of years, which is where I found the diagram below.  Notice the x-axis of “Time degree of trust and complexity”.


As one commenter in the LinkedIn group states:

I tried CPFR with one of my biggest customers. It was failed before it started to work. The customer’s only interest was to put all the risk/cost on my side. They even didn’t want to be [bound] by their own plan. 

Where’s the trust in that statement!  Another commenter on the LinkedIn group, whom I presume works for a retailer, states (with minor edits from me):

I don’t think CPFR can work… Retailers also don’t receive any info from the consumers of what and when they will be purchasing. I think [the] process [should] start [with] the “Voice of the Customer”. … ( I want to find the product I am looking for on the shelve and buy and take it home if possible).

To bring it all together a 3rd commenter stated that:

… forecasting and planning process is used to set sales targets, rather than predicting demand…

Lora Cecere’s opening statements are also very direct.

Go to any supply chain conference, and you will hear it.  Yes, the term collaboration is bandied about. It is over-used and often over-hyped in discussions largely without meaning.  So, what does it mean?  And, what happened to the supply chain collaboration initiatives of the 1990s? Let’s start with the definition.  The greatest success in supply chain relationships is when true collaboration happens.  What does it look like? It is a when a sustainable win/win value proposition.   Six elements are required:  resources, skills, joint vision, leadership, a plan, and aligned incentives. The problem is that the so-called “collaborative programs” of the 1990s focused solely on process missing the mark on these six elements.  The tenants of VMI and CPFR were well-intended, but they fell short in building true collaborative relationships.

And yet the potential value is enormous in terms of both reduced inventory and in terms of supply chain agility, not to mention the cost of ‘policing’ the supply chain relationships. The concept of the Bullwhip Effect has been around for 50 years now, having been defined by Jay Forrester in 1961 in his seminal book ‘Industrial Dynamics’. What amazes me is that the central lesson learned from the exercise is that end-to-end visibility, in other words a rudimentary form of collaboration, has an enormous positive effect on the efficiency of the supply chain.  So is it really just power and control, or lack of trust, which is preventing the adoption of this core learning?  And yet the evidence is difficult to refute.  In an article titled “Supply Chain Management Application Trends, 2010” which was published by Gartner on Nov-30, 2010 (subscription required), the authors Dwight Klappich and Chad Eschinger included the following diagram, clearly indicating a much lower level of interest in “Inability to coordinate and synchronize end-to-end supply chain processes” (in other words cross-company collaboration) than other areas, although “Lack of internal, cross-functional collaboration and visibility” is clearly an opportunity for collaboration within the 4 walls of an organization.   What really jumps out at me in the diagram is that the biggest issue is “Forecast accuracy, demand variability”, exactly the point raised by one of the LinkedIn commenters.  But didn’t the Bullwhip Effect show 50 years ago that visibility and collaboration across organizational and functional boundaries, particularly with respect to the demand signal, leads to a far more effective and efficient supply chain?


In a recent conversation with Lora Cecere we agreed that our guestimate, based upon discussions with customers, is that the inquiry-to-quote-to-order process, in other words the decision process, often takes longer than the order-to-delivery process, in other words the physical process. How sad is that? This is where a great deal of the agility can be extracted from the supply chain processes, especially when we hear of customer expectation of shorter order lead times.  George Stalk was writing about time-based competition 20 years ago in which he captures the basic tenets of time-based supply chain inefficiencies in the following 4 rules:

  • The .05 to 5 Rule
    Most products and many services are actually receiving value for only 0.05 to 5 percent of the time they are in the value-delivery of their companies
  • The 3/3 Rule
    The waiting time has 3 components, which are the time lost while waiting for:
    -  Completion of the batch a particular product or service is part of
    -  Completion of the batch ahead of the batch a particular product or service is part of
    -  Management to get around to making and executing the decision to send the batch on to the next step of the value added process
  • The ¼-2-20 Rule
    For every quartering of the time interval required to provide a service or product, the productivity of labour and of working capital can often double, resulting is as much as a 20% reduction in costs.
  • The 3 x 2 Rule
    Companies that cut the time consumption of their value-delivery systems experience growth rates of 3 times the industry average and 2 times the profit margins

I wonder how much of the lack of adoption is due to people being used to the ‘open’ world provided by the internet?  I think that the First Things Monday blog (registration required) of Dec-12, 2010 titled “Reader Response to ERP in the Cloud” by Dennis Gaughan goes quite a long way to suggest that social media concepts combined with cloud computing are beginning to increase the level of interest expressed by enquiries:

They would like to see applications that blended business processes from ERP with social networking technologies and the cloud to truly deliver a new way of collaborating with their trading partners. To quote one reader, “The power of a supply chain which identifies and allows various sourcing options based on product availability, right now, is compelling.”

And yet there is an argument raging between Dennis Howlett ( and Andrew McAfee (  I commented on Andrew’s blog with reference to process/decision vs physical lead times.  Dennis is arguing, I believe, that trust is a major barrier to adoption of Enterprise 2.0, or Social Business, concepts within an organization, let along across organizations. Andrew McAfee on the other hand points to real examples where value and trust have been delivered by Enterprise 2.0 technology, although, unfortunately, none of his examples are within the supply chain space.

I don’t believe these positions need to be mutually exclusive or diametrically opposed, or argued quite as ‘loudly’ as they are by Dennis and Andrew.  I think people largely come from different experiences and some are very distrustful of all things electronic let alone on the internet.  As an example I will use my wife’s resistance to TiVo.  She is a classic example of someone who should not be given a universal remote.  In 2003, when we first got TiVo, she had only just mastered setting timed recordings on the VCR.  I knew that presenting her with the TiVo remote with about 25 buttons would be the wrong approach.  Instead I showed her what she could do with TiVo by recording films with actors that she liked, without having to page through the 120 page TV guide. Once she saw this value she was willing to tackle the complexity of the TiVo remote and expanded her use to much more complex use of TiVo.  Too many of us technologist (yes, I am one too) start with the cool technology stuff, forgetting to start by articulating and getting buy-in to the business benefit. Put differently, in building trust that the collaboration is of both individual and mutual benefit, and that technology is not a barrier but an enabler.

So I am optimistic that a combination of unique circumstances of both business drivers and available technology will lead to increased adoption of collaboration within the supply chain space, both within an organization across functional boundaries, and across organizational boundaries.  I believe the diagram above from the Gartner article supports the business imperative in spades.  After all, the challenge of “Lack of internal, cross-functional collaboration and visibility” is tied directly to S&OP because an absolutely key aspect of S&OP is internal, cross-functional collaboration.  And we hear from all analysts that S&OP is the top enquiry by far. I also think that we need to restate CFPR as S&OP across organizational boundaries.

The business case is there.  What we need to do is to provide tools that make the collaboration feel natural.  I think that the very rapid adoption of social media concepts inside the workplace, such as Salesforce Chatter, indicates that the users are ready. To repeat, the conclusion I came to is that the real barrier to collaboration is not technology, but trust.  How can we build the trust to make collaboration a reality?

Posted in Milesahead, Response Management, Supply chain collaboration

Transforming the Pharma Supply Chain Part 2

Published December 16th, 2010 by Kerry Zuber 0 Comments

Taking note of best practices across industries

As mentioned in Part 1 of this post, despite the unique aspects of the Pharma industry, the bulk of the supply chain management issues are largely common to many other industries.  And without the same degree of supply chain focus that is present in the high tech space for example, the net result generates a degree of waste almost unfathomable by those outside the industry. The chief question is, “can you achieve an acceptable level of supply availability without the waste?” It’s understood that the definition of “acceptable” ranges from 100% availability for some life sustaining medications to more conservative fill rates for OTC generics. There are enough examples of supply chain mastery in the high tech and automotive industries to suggest the answer is an absolute yes.

The high tech and automotive industries have for years been focused on adopting the precepts of Lean that deal with the elimination of waste and the rapid reaction to change. That is not to say that Pharma industries haven’t leveraged lean principles, but the key difference has been the high tech focus on the entire value chain rather than individual sub-processes. An operational sub process focus can yield what appears to be cost improvements, but without addressing the broader connection to customer demand patterns and other supply chain steps, they often fail to significantly affect the overall cost. It is the consideration of the cost trade-offs of the entire supply chain’s ability to meet demand that seems to be missing.

It is in the area of demand planning where the difference is most evident. In high tech, with the economic pressures to minimize the inventory investment, the ability to rapidly and economically adjust to demand shifts is a major factor in business performance. Saddled to that is a focus on improving forecasts accuracy through investments in collecting and analyzing more meaningful data , while also more broadly collaborating on a consensus plan. As part of this effort, many leading high tech companies have embarked on collaborative forecasting and planning with distributors and sub-contractors.

In Pharma, the inventory buffers make similar investments seem less important. A February 2010 article by Wayne McDonnell of Gartner Research, “Just how long do we have to wait for True S&OP in Life Sciences,” proffered that the two most important areas where life sciences companies need to invest is on improving forecast accuracy and end to end supply chain management.

Pharma companies have also followed many of the outsourcing trends as high tech with essentially the same consequences. Limited visibility and collaboration challenges in synchronizing the supply chain when volatility strikes. As the pressure to control costs and optimize inventory increase, these challenges take on increased importance. Global supply chain visibility and synchronization has been on the strategic initiative list for high tech companies for several years, while it has gained importance in the Pharma space much more recently.

In recent years, Pharma companies have begun to recognize the potential of adopting a high tech approach to both demand planning and supply chain management. Given the pre-existing emphasis on fulfillment, the improvements being sought are more in the areas of end to end cost and working capital turnover. The key to achieving those are through better demand management and an end to end supply chain management focus.

Experiencing escalating costs and working capital strain, companies are rethinking their supply chain model, changing their approach and increasing their capabilities in order to drive better alignment and performance. Evidence of the change is seen in recent hiring trends with executives and middle managers from the high tech and other industries being lured into the Pharma space. As one example, a January 2010 article in the Wall Street Journal discussed how Mr. Jimenez, the new CEO at Novartis, one of the largest drug companies, had spent most of his career at consumer packaged goods companies, and thus, one would believe that a primary benefit of the appointment would be that Mr. Jimenez could bring a cost and efficiency focus to the role.

As Pharma companies make the transition to better forecasting methods and end to end supply chain management, a new era of cost competitiveness will ensue. With lower inventories, cash will be freed up to address growth and investment opportunities, but it will also introduce the need for competencies in Lean and Response Management to ensure that fulfillment objectives are not compromised. Analysts have for years heralded what the transformation can deliver —$43 billon in working capital alone according to the A. T. Kearney analysis. With the recent influx of supply chain expertise from outside the industry it could be that the transformation will finally take a leap forward.

Posted in Pharma and life sciences supply chain management

Transforming the Pharma Supply Chain Part 1

Published December 15th, 2010 by Kerry Zuber 0 Comments

Can you achieve an acceptable level of supply availability without the current waste?

There is no question that the Pharma industry must deal with a unique combination of supply chain and regulatory issues to meet its obligations to consumers, supply chain partners and shareholders. For some biotech companies, availability of their products are literally a life saving necessity and disruptions in the supply chain can result in a form of supply triage that is uncomfortable to even consider.

Unlike other industries, the Pharma industry has traditionally treated supply availability as a prime factor, even to the extent that several months of safety stock was not considered excessive. While in the other industries, best in class performance inventory turnover performance is double digit, the Pharma companies seem satisfied with low single digits despite the impact on cash and working capital.

In an April 2010 article in Pharma Pro, entitled, “How to Unlock $43 Billion in Value by Improving Working Capital Management,” A.T. Kearney reported that an analysis of Pharmaceutical companies revealed an average inventory level of 170 days.

Supply availability though is just one key difference to other industries. In a number of the Bio-tech companies, they’ve had to invent equipment and manufacturing processes to produce the new wonder drugs. Early manufacturing is just targeted on producing enough to satisfy trials and is less focused on cost and efficiency. Unlike engineering changes in the high tech industry that change the content of a product, changes in the Pharma space usually target the cost and yield of the manufacturing process. To add to the complexity, these changes must satisfy the quality control requirements of regulatory agencies. The approval process can take months and uncertainty in the timing creates a variety of risk management issues. In addition to the regulatory control over manufacturing, there are different regulatory issues to face in each of the market regions that govern a wide variety of factors including packaging, labelling and shelf life requirements. Combine these factors with the extremely high margins on non generic drugs, and it’s no wonder that the Pharma industry has historically put little emphasis on minimizing the non-production aspects of the supply chain costs.

BUT despite the unique aspects of the Pharma industry, the bulk of the supply chain management issues are largely common to many other industries. Planning for raw materials, dealing with manufacturing constraints, establishing and monitoring distribution inventory levels, and dealing with significant market demand volatility, are just a few. It is important to note that the dynamics that have introduced unparalleled volatility in the high tech industry (short life cycles, internet purchasing behaviors, and intense price competition), have had less of an impact on Pharma, but other factors have achieved much the same result.

Increased global competition, economic conditions, and changes in both regulatory factors and insurance coverage have collectively produced higher levels of demand volatility. Without the same degree of supply chain focus that is present in the high tech space, the net result generates a degree of waste almost unfathomable by those outside the industry. The chief question is, “can you achieve an acceptable level of supply availability without the waste?” It’s understood that the definition of “acceptable” ranges from 100% availability for some life sustaining medications to more conservative fill rates for OTC generics. There are enough examples of supply chain mastery in the high tech and automotive industries to suggest the answer is an absolute yes.  The next question is “How?” 

Stay tuned for Part 2 of this discussion tomorrow.

Posted in Pharma and life sciences supply chain management

Supply chain visibility is vital, but the larger business goal is agility

Published December 14th, 2010 by Bill DuBois 1 Comment

I recently ran across some research that really has me thinking. The IBM Institute for Business Value surveyed 664 supply chain management executives in 29 countries around the world, and the results are pretty much what you would expect. That is, those executives cited global economic turmoil and uncertainty as the driving factors behind their three most significant supply chain challenges.

Those top three challenges are:
Volatility—driven by global complexities and fluctuation in customer demand
Visibility—specifically the need for accurate, time-sensitive information
Value—continued corporate pressure for supply chain management and operations to create enterprise value

Those are indeed, significant obstacles. Fortunately, considerable progress can be made addressing them through the use of a supply chain management solution, and, more specifically, S&OP tools.

There’s been quite a bit of discussion about demand volatility here on this blog and in the Supply Chain Expert Community. For instance, Lora Cecere from the Altimeter Group addressed the subject in a webinar titled, “What S&OP capabilities matter most?” Trevor Miles has had some good posts on volatility too.

What Lora, Trevor and others have noted, is that in recent years, demand has not only fluctuated more significantly than in the past, but the frequency of change has also increased. The result is that forecasting by looking only at historic demand patterns is no longer sufficient. What’s needed instead, is the application of a robust what-if? capability to do range forecasting. That way, rather than a single number forecast, users can also test upside and downside scenarios to evaluate potential risks and mitigate against them.

It isn’t surprising that visibility—or, more accurately, lack of visibility—was cited as the second most prominent supply chain challenge by respondents in IBM’s survey. As today’s supply chains become more complex, visibility becomes more important. This is particularly true in industries such as high-tech electronics and consumer goods, where brand owners and contract manufacturers face high demand volatility and rapid product evolution. They also have increasingly complex operations where many critical activities take place outside the traditional four walls of the enterprise, and there are many geographically-dispersed sites and/or partners using disparate data systems.

I’ll argue, however, that the real challenge isn’t to simply gain visibility. It is a pre-requisite to the end-goal, not the goal itself.  Sure, visibility is vital but the larger business goal is to improve agility.

Many will promote “visibility” solutions and will tie that to statements like “sense and respond.” The problem is few, if any, are actually providing tools to enable the response process. They provide a limited level of visibility and leave users to determine how to benefit from it.  Visibility without the tools to drive action gives only minor advantages to the organization. One needs to be able to alter and analyze information, not just see it.

I’ll also add that collaboration plays a critical role. Having access to “actionable” supply chain information can set the stage for more meaningful and effective interactions between stakeholders based on informed decisions whereby the impact of decisions are understood and action plans are clearly defined.  To truly improve supply chain performance—and ultimately address that unrelenting pressure to add enterprise value—a company must first gain supply chain visibility, but then they must be able to collectively leverage that data to make rapid decisions and act accordingly. 

That is true value.

Posted in Miscellanea, Response Management, Sales and operations planning (S&OP), Supply chain collaboration, Supply chain management

4 common reasons why companies evaluate products from their ERP vendor first…even if they don’t want to

Published December 10th, 2010 by Monique Rupert 0 Comments

I just read an article titled:  “Throwing Enterprise Software Vendors Under the Bus” by Thomas Wailgum of Enterprise Software Unplugged on  Obviously, I work for a SaaS based software company and we compete against some modules from the big ERP vendors.  We work with very large companies who primarily deal with Oracle or SAP.  Whenever there is an IT need most of the companies, by default, will evaluate the products from their ERP vendor… even if they don’t want to.   These are some of the most common reasons I hear from these customers on their evaluation criteria (this is not an inclusive list):

  1. Common platform (or may be called Standard Platform):  Most big companies are trying to standardize their IT requirements on one or two “common platforms”.  Typically this means a software platform that has broad functional capabilities that can solve multiple business problems.  If a company had a new business need they would first evaluate whether one of their common platform solutions can meet their requirements prior to evaluating a point solution.  In theory, this should save the company money on integration, hardware and licensing costs.  However the company will likely have to forego some functionality.  If a software vendor can be designated a common platform, then they have a better chance of being more broadly deployed.
  2. Technical infrastructure and scalability:  The big ERP vendors have done a very good job marketing their technical infrastructure to ensure very large deployments of software.  They have benchmarking services to prove scalability.  Although these companies are strong on infrastructure and scalability, large customers still have issues with performance on some applications.  It is important for any other software company to be able to address these concerns and compare their solution to the big ERP vendors.
  3. Job security:  The employees in an IT department typically want to work with name brand software companies so they can make themselves more marketable.  They don’t want to become experts in a little known software that won’t help them get their next job.  Many CIO’s have staked their careers on implementing their ERP solution and don’t want to admit it cannot meet all their needs.
  4. Costs:  Big ERP companies many times “throw in” extra modules in a bundled license agreement with the hope that the customer will sign up for the M&S cost if they use those modules. (see John Westerverld’s recent post about M&S – that’s a whole discussion on its own)  Regardess, the extra “free” modules make any ROI evaluation between software vendors look better for the ERP vendor.  Although, there are typically many “hidden” costs in implementing new modules.  For example, some of the modules actually require a fairly heavy integration effort even though it is on the same platform because they are not native products to the core ERP engine.  Being able to show Total Cost of Ownership and ROI will be important for any software company wanting to compete against the big guys.

In order for a software company to be successful against the big ERP vendors they will need to address these concerns.  Certainly the above concerns can be overcome, but the software vendors should know the bias they are up against.

What reasons have you seen on why companies don’t want to leave their ERP provider to choose a better solution?

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