More importantly though, I want to explore the difference between product design and supply chain because many of the mobility providers have had a rocky ride over the past 3-4 years, and yet many of them have excellent supply chains, and have been recognized by Gartner in the Gartner/AMR Supply Chain Top 25 over the past years for this excellence.  I have compared the list from 2008 to 2011 to highlight the fortunes of the mobility companies, which are highlighted in red below.  (I’ve excluded Microsoft from the list of mobility providers because of the failure of the Windows phone and because mobility represents such a small portion of their revenue. I’ve included Samsung simply because of the success they are having lately with their Android phone and tablet, but in reality Samsung has a much broader product portfolio than Apple, Nokia, or RIM, making a direct comparison difficult.)

Of course, many people, including me, have criticized the Gartner/AMR Top 25, but it is a consistent methodology that emphasizes both supply chain effectiveness and product innovation. It is in this regard that I want to comment particularly on Nokia and RIM. But the stock market is really the comparison that matters.   According to Google Finance, in the period since Jan 2005 the Dow Jones is up 17%, Apple is up 1213%, Nokia is down 67%, and RIM is down 56%. How I wish I had invested in Apple, even as late as in 2008.

While Apple has been the consistent winner of the Gartner/AMR TOP 25 for the past 4 years, Nokia placed 2^nd in 2008, 6^th in 2009, 19^th in 2010, and dropped off the list in 2011, even though from a stock price perspective Apple was out performing Nokia even in 2008.  Likewise, RIM wasn’t even ranked in 2008 and 2009, leaped into 9^th place in 2010, and up to 4^th in 2011, even as their stock price was taking a beating.  So Nokia and RIM were doing something right in their supply chain if they could be ranked as highly by Gartner in a comparison that includes product innovation.  And they were, both companies showing a lot of innovation in their supply chains.

If we look at the 2 graphs below we can see why Apple is the clear supply chain leader with much better performance over the past 3 years in measures such as RONA, inventory turns, and DPO/DSO ratio. But Nokia’s and RIM’s performance are very good with inventory turns greater than 15.  Even Nokia’s RONA is very good despite their relatively poor performance against Apple and RIM, which can be explained by the fact that Nokia’s manufacturing is mostly insourced while Apple and RIM have almost 100% outsourced manufacturing. But it is in Cash-to-Cash (C2C) that we can see the real dominance of Apple in terms of supply chain efficiency and effectiveness. They have reduced their C2C from -20 days in 2005 to an astounding -60 days in 2011. At their current cost of goods sold of $25.63B per quarter, the C2C improvement represents an additional $11B of cash released on an annual basis. Assuming a WACC of 10%, that represents a savings of $1B, which can fund an awful lot of product research or marketing.

Apple notwithstanding, because it is really an outlier, RIM and Nokia have posed very good supply chain performance numbers that, when compared with other companies, fully justify their ranking in the Garter/AMR Supply Chain Top 25.

It is when we look at Nokia’s and RIM’s gross margin and operating margin that we can see the net effect of their strained product portfolios.  In a 6 year period Apple has achieved a 10 % improvement in gross margin and a 15% improvement in operating margin, compared with  -15% and -25% for RIM, and -5% and -15% for Nokia. But I’ve got say that I still find the Blackberry more functional from a business use perspective and the Nokia a lot more intuitive from a novice user perspective, although these are the exact product characteristics that are hampering their growth.

I really hope that both Nokia and RIM manage to survive their current reversals in fortune because they are great companies with very efficient supply chains. They have fully justified their prominence in the Gartner/AMR Supply Chain Top 25.

I would like to expand on a couple of these points, focusing on optimizing the supply chain through the use of collaboration, simulation, and scenario comparison utilizing modeling tools.

The supply chain network is composed of many different components acting in concert to deliver the required goods and services at the right time. The better these interdependent relationships are understood, the better the supply chain can be optimized. This raises the question how best to optimize such a complex set of data points.

In order to get an accurate simulation, you must be able to obtain accurate data about each node in the network, and then utilize software to model it. These nodes can include, but are not limited to:

• manufacturing plants,
• supplier plants,
• sub contractor plants,
• warehouses, and
• transportation routes.

This requirement would suggest that any simulation model must be able to incorporate multiple disparate data sources in a relatively easy and timely manner. Important data to obtain would be:

• lead times,
• inventory levels,
• in transit times,
• associated costs,
• quality levels, and
• service levels.

There are many others that could also be included to give a more accurate picture of the network.

Once this data has been obtained (which may require some effort, especially with off shore suppliers), the next question then becomes, what do we do with the data? This is where the requirement for multiple scenarios becomes critical.

Because these networks can be extremely complex with many factors influencing outcomes, we must have the ability to compare many different scenarios in order to determine a path forward. One scenario may give us a lower overall cost, but poorer customer service. Another may result in cheaper raw material costs, but lower quality levels and increased transportation costs. All these outcomes must be weighted in order to determine the most optimal design, -this requires some way to be able to compare multiple scenarios in a clear and efficient manner.

The next step would then be to examine each scenario, and determine if the best parts of each can be combined into one ‘super’ scenario. As an example, one scenario may have a supplier with lower cost, but higher transportation costs. What if sourcing is split between a low cost/high transportation supplier and a higher cost/low transportation supplier? By managing the sourcing between the 2, an optimal outcome may be achieved (happy medium). This can only be determined by developing a complex model with multi-sourcing.

If you take this case and apply it across the network, the number and complexity of the inter-relationships can soon become mind boggling. This is why a multi scenario engine which can rapidly calculate the various outputs of the model from its inputs is so vital. In order to implement the optimal supply chain network, it must first be designed as a whole to deliver the optimal results.

Once the supply chain network has been successfully modeled, a powerful tool is now available for what if analysis. The maximal use of this tool can be realized by incorporating continuous improvement into the business development cycle and optimizing the network on a regular basis. But in order to make this an effective tool for continuous improvement, a plan must be generated quickly and easily analyzed, as time and resource constraints limit the amount of time to turn around the results and push improvements to the network. This is why speed and performance matter when implementing complex modeling solutions.

Because the only way to realize the benefits of an optimal network model is to implement it, collaboration among all the players in the network (inside and outside the enterprise), is vital. This leads us to another key criteria for a simulation system - the ability of many users to access and collaborate on the development of the network model.

Once the simulation, model, and collaboration pieces are in place, it raises the question: Can this environment be used to model other complex systems as well as the supply chain? What about the ‘sales chain’, the complex relationship between you and your customers? What about the complex network of relationships that exist between an enterprise’s internal resources (employees) and the enterprise? Financial models? As can be seen, there are a myriad number of networks in the modern world that can be modeled for the purposes of increasing efficiency, and thereby reducing costs or improving service levels.

Although there may be no such thing as a perfect forecast, there are plenty of opportunities for improvement and managing demand in support of a more cost-effective supply response. Better collaboration between trading partners is the necessary next step toward waste elimination in the value chain.

Maximizing value from the supply chain won’t be reached without improved collaboration between trading partners.

In fact, Mike identifies the lack of collaboration between trading partners as the primary cause of demand volatility. (I agree that the lack of demand visibility increases demand volatility, but there are other industry dynamics that are increasing demand variability.)  Of course, visibility and collaboration are the key messages behind The Beer Game (or beer distribution game) which was originally invented in the 1960s by Jay Forrester at MIT as a result of his work on system dynamics to illustrate the bull-whip effect.  Absolutely critical to a smoother functioning supply chain is demand visibility across the entire supply chain.  Of course visibility isn’t a very mature form of collaboration, but it is at least a start and a necessary precursor to more mature forms of collaboration. And let’s be honest, after 50 years we still haven’t really got to effective demand visibility, although there have been improvements.  To get some estimate of how well your company is performing in this regard you can take the Gartner Demand-Driven Value Network (DDVN) maturity self-assessment.(Registration or Gartner membership required.)

But it isn’t just so-called Easy-West collaboration between customers and suppliers that is required.  I would be happy to start with the so-called North-South collaboration between strategic and financial plans, usually the focal area of the executive suite and Finance, and operational plans. Some analysts and commentators have called this integrated business planning, which also dates in concept from the 1960’s. I’d even settle for East-West collaboration between demand and supply functions within one organization, including Gartner’s stage 4 Sales & Operations Planning (S&OP) maturity. There is no inter-company process that is a better measure of collaboration than S&OP done well.  According to Jane Barrett of Gartner, most companies are stuck in stage 2 maturity.  This is largely due to the inertia and resistance to change so prevalent in many companies.

But how is it that 50 years on from Jay Forrester’s work we are still struggling with this issue? My opinion is expressed in a blog titled “Do you trust yourself to collaborate? The real barrier to collaboration is not technology, but trust”.  Let’s face it, technology can always be improved, especially the user experience. But the capabilities of the technology available for inter-company and intra-company collaboration exceeds the willingness of organizations to share information at the moment.  As Mike Burkett points out, huge gains can be achieved by collaboration, so why don’t companies try to capture these benefits?  My opinion is that the issue is the same that is preventing them moving from stage 2 to stage 3 S&OP process maturity, namely that they simply want to automate their existing manual processes and don’t realize that effective collaboration requires both new ways of working and supporting technology capabilities. 

Nothing captures this better than a Henry Ford quote that “If I had asked my customers what they wanted, they would have said faster horses.”  There is a strong synergy, even symbiosis, between technology and process.  In a great slide show titled “What if Peter Drucker taught Enterprise 2.0?”, Mark Fidelman states that

Neither technology nor people determines the other, but each shapes the other.

But let us recognize that the financial and operational risks of collaboration are tangible and can be high.  There is a good series on collaboration in the Harvard Business Review.  The one I like best dates from June 7, 2011 and is titled “Collaboration is risky.  Now get on with it.”  The author, Whitney Johnson, writes that

Why is teamwork so difficult?

Because collaboration is actually a pretty risky business. Perhaps, like me, you are generally of the mindset that two heads are better than one. But because your ideas frequently get co-opted, there’s a risk-reward imbalance that makes you reluctant to engage. Or maybe you’ve reached out to a potential collaborator only to have your lack of expertise exploited. So, rather than ever again experiencing the one-two punch of ignorance and vulnerability, you’d prefer to soldier on alone. In both instances, the fundamental barrier to collaboration is a lack of trust.

While writing about individuals within a group, clearly Whitney’s observations and opinions are very applicable to collaboration between functions and organizations.  Her prescription is to

1. Start with simple exchanges where the cost of betrayal is low.
2. Remember that our collaborators are competent.
3. Don’t take advantage of our collaborators’ deficiencies.
4. Give others their due, and expect yours in return.

Sound advice.  Yet so difficult to put into practice.  The comments section is well worth a read too, including links to some interesting materials.

Mike Burkett concludes his First Things Monday contribution with the observation that

By closing gaps between partner nodes in the supply chain, there’s an opportunity to address the unnecessary waste across the value chain.

These are the hard benefits of supply chain collaboration.  They are real and they are achievable.  Yes, the risks are real, but the rewards are equally real.

The complexity of the electronics supply chain is such that, six weeks on from the earthquake, no one is sure what its effects will be on their businesses…
For an industry which manufactures to tolerances measured in billionths of a meter, in which the researchers win Nobel Prizes and the salesmen have PhDs, it’s anomalous that it can’t forecast, plan, locate, track and measure its output.

The cause of the supply chain opacity referred to by David is the degree of outsourcing, coupled with ever increasing product portfolio complexity, which is due to mass customization and shortening product life cycles. Statistical forecasting is a ‘large number’ tool that requires long histories and frequent sales to achieve a high level of accuracy. Digital cameras have life spans of six months and less. Smart phones have a life span of 18 months and less ― and this is decreasing even as the number of models and model variants explodes. The shorter life spans means there is little history to go on and the explosion of model variants is greater than the increase in sales volume. It is no wonder that consumer electronics companies can seldom get forecast error, as measured by MAPE at a month lag, below 50 percent. Forecasting at the product family level only makes matters worse because this hides trends that are critical to determining component and capacity requirements, even though forecasting at the product family level may lull you into a false sense of security by reducing forecast error.

Yet as stated by Research in Motion, the Blackberry owners, in a webinar hosted by SCMWorld on Apr 28, 2011, product portfolio complexity is required to compete in a consumer market with ever changing requirements. This is in stark contrast to many pundits who advocate reducing supply chain complexity, the primary cause of opacity, by reducing the product portfolio.  I am the first to agree that a sound product portfolio analysis is something everyone should do, but outsourcing isn’t going away, neither is mass customization.  So I say embrace complexity by providing visibility.  But in today’s highly outsourced environment visibility must span several tiers of the supply chain from customer through OEM to contract manufacturer and on to the component suppliers.  If you have distributors, then at least get a ‘sell through’ measure of demand, not just a ‘sell in.’

But access to data across the supply chain is not visibility. Without a manner in which to respond rapidly and profitably to actual demand, access to data adds nothing. But I agree, access to information across multiple tiers of the supply chain is a start. Being able to detect changes from the plan, understand the consequences of the changes on customer commits, capacity requirements, or component requirements, and evaluate alternative courses of action in both financial and operational terms quickly and effective is the clue to gaining visibility.  Only this will reduce the opacity in today’s supply chains.

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.

There is, however, a second required element for successful outsourcing. It’s the human aspect, which sometimes proves to be more challenging than implementing software. In fact, various research indicates that chief among the barriers to globalization are: lack of supply chain flexibility, lack of internal competencies to manage external partners and a reliance on partners who are unable to meet flexibility requirements.

A recent SupplyChainBrain article reports on a new paper that goes even further, asserting that for outsourcing to truly be effective, an organization must not rely solely on contracts with suppliers. Instead, companies must also work to foster an informal supplier-buyer relationship.

Chwen Sheu, Paul Edgerley Chair in Business Management, professor and interim head of the department of marketing at Kansas State’s College of Business Administration, studied how nearly 1,000 companies worldwide manage outsourcing, and co-authored a paper—“What makes outsourcing effective- a transaction cost analysis”—along with John Wacker from Arizona State University and C.L. Yang from Chung Hau University, Taiwan.

Data was collected and analyzed from 970 manufacturing firms in 17 countries, and the researchers found that most of those organizations depend on both legal contracts and an informal supplier-buyer relationship. Sheu says both methods are effective, but informal relationships with suppliers deserve more attention from management since in outsourcing, it’s impossible to cover every risk and outcome contractually.

When an unexpected event occurs, and the contract doesn’t specify how to respond, it’s imperative to be able to sit down and resolve the issue with suppliers, Sheu says. This is really a trust and information sharing issue, which allows both parties to deal with unforeseen risks and uncertainties more effectively. In a truly trusted relationship both parties recognize that all decisions need to be mutually beneficial in order to achieve success.  The people are the difference between a satisfactory relationship and an exceptional one, where both parties will over achieve to ensure their partner’s success.

It’s important to note that not all of a company’s suppliers need to be involved in this level of collaborative discussion. Instead, it’s really only necessary to closely communicate with a few, trusted suppliers. For instance, your company may purchase a number of commodity components from several suppliers. It isn’t necessary—or appropriate—to closely collaborate with all of them.

On the other hand, you should collaborate closely with those few key suppliers that represent the majority of your spend on components, supply components used in products that represent a major portion of your company’s revenue, and supply long lead-time components—especially when there is a potential for excess and/or obsolete inventory.

Successful outsourcing requires developing better relationships with long-term, key suppliers. When that’s done, the brand manager and supplier can share business strategies, mutually evaluate risks and threats, and jointly investigate opportunities. In the end, that allows both companies to realize significant benefits.

Wednesday, November 17, 2010 at 11:00hrs New York (16:00hrs London, 17:00hrs Paris)

with presenters:

• Dr. Hau Lee, Thoma Professor of Operations Information and Technology,  Stanford Graduate School of Business
• David Smoley, Senior Vice President and Chief Information Officer, Flextronics International
• John Sicard, EVP Marketing, Development and Service Operations, Kinaxis

Register today!

Here is a little more about the session…

Translating business drivers into technology requirements: How to support today’s S&OP and SCM landscape

As a leading EMS provider, Flextronics is no stranger to supply chain pressures. Short product life cycles, demand volatility, supply shortages – all of which must be managed within a supply chain that crosses organizations, geography and time zones. As a result, there is a tremendous need for supply chain agility. One of the most fruitful ways to improve agility is to reduce decision latency throughout the multiple layers of the supply chain and throughout the various stages of the S&OP process. From a technology perspective, this has created an urgent demand for:

• Visibility – across data sources, systems, and organizations
• Collaboration – between functions and trading partners, often across three tiers of the supply chain
• Identification & Alerting – easy and early identification of people who are impacted or can provide insight into decisions
• ERP agnostic analytics – for rapid evaluation of decision alternatives across partners using different systems within the multi-tier supply chain

I think that most of us would agree that ideally, we would have a sound plan where there is accurate demand (forecast and/or actual), adequate resources and capacities are in place both in-house and at suppliers, and all the supply chain is on board and executing to the plan.  In reality, there is a lot of expediting that occurs, at least in my experience (the extent of which depends on the industry and the complexity of the products and the supply chain.)  A lot of manufacturing companies even have a formal position with a job title something like “Material Expediter” or “Production Expediter” (although the actual job descriptions can differ from what I am describing).

What I have found in working with some customers who do a lot of expediting, is a basic lack of maintaining data accurately in their formal ERP/MRP system.  A lot of the “planning” tends to occur off-line in Excel spreadsheets or other tools.  This may work in some isolated areas, but from an overall enterprise perspective, much of the supply chain does not have visibility into these off-line plans.  I correlate this to Project Management on a large project where there is no up to date project schedule that the entire project team can work to.   Team members work tasks that they are directed based on meetings, phone calls and other types of somewhat ad-hoc communication. 

This can be somewhat effective, but not having the formal MRP system reflecting the current plan disables the capability to orchestrate the entire supply chain and efficiently execute the plan.  This leads to a lot of expediting rather than planning and executing.  Why don’t we always keep the formal MRP system up to date?  There are lots of reasons, including:

1. too time consuming;
2. off-line tools are easier and more flexible; and
3. certain processes or functionality is not supported in the formal system.

An example of # 3 above, is provided in a blog post from a colleague of mine called Do YOU have enough Supply?   This describes a process to allocate limited supply to demands that recently, seems to becoming more prevalent in certain industries.  A process like this may not be supported in the formal MRP system, so it is likely done off-line.  Changing or enhancing the MRP system to support new functionality generally takes some significant time and money, and usually has to compete for priority with other fixes and enhancements needed.

I know that many of you will agree that this expediting approach is far from ideal, and also may say “not us, not me”.  But I also know from experience that this occurs and sometimes with some very practical reasons.  In situations like this, what can help solve the problem is a system with capabilities in a couple of key areas:

1. Detect and report data integrity issues in the MRP system for clean-up
2. Easily configurable to support additional planning functionality
3. Available for sharing and collaboration across the supply chain

I would like to hear any insights, experiences and suggestions you may have regarding this expediting versus planning situation.

Here’s the big question:  Will companies think differently after suffering the consequences of this natural disaster?  What will they do different?

I don’t think the answer is building more just in case inventory. In order to stay competitive supply chains have to be lean. (In fact, they are becoming even leaner with late stage postponement to satisfy increasing levels of customization on consumer goods.)

Here are some questions for consideration:

1. Can you proactively analyze and understand the risk of unplanned events?  This may be the upside or downside in demand or supply disruptions. This also includes the identification of sole sourced material.
2. Do you have the visibility and access to information in your supply network that you need? More and more companies are looking for a global view of all of their inventory with the need to rebalance as the demand and supply fluctuate
3. Do you know what to do when you have a problem that you just can’t solve?  When a volcano happens there is not much you can do about it. The question is are you making the best use of the supply that you have? How do you want to prioritize demand and allocate your supply? How quickly are you able to make these decisions?

While there may never be another volcano that disrupts the supply chain, there are daily disruptions that affect companies every day, and that taken in sum can have a material impact to the business. How do you deal with them?  Send in your stories!

A big limitation of Excel in my view is that it cannot mimic the analytics in the company’s source ERP system.  Why is this important?  If someone is using Excel to make business decisions without all the capabilities the ERP source system has, then they may not be making the right decisions.  How can you make planning decisions if your spreadsheet doesn’t take into consideration functionality like sourcing rules, constraints and order priorities?

A company’s supply chain map is very complex, typically there are internal manufacturing data sources, external manufacturing data sources, inventory site data, etc.  It is possible to get data from multiple sources into Excel, but the big challenge is that the data is not always the same from each source system, so many organizations may have multiple spreadsheets to perform the same function/analysis.  But can any of those spreadsheets be truly accurate if they don’t show a true picture of the whole supply chain?

It is almost impossible to control the integrity of spreadsheet data and access to the spreadsheet.  With multiple people accessing the spreadsheet and no security, how can anyone have any confidence in the data?   In addition, most spreadsheets need to be reviewed by many people which typically requires pushing the spreadsheet around.  Without system standard security, data integrity could be an issue and auditing who made changes could be an issue.   How can there be a high level of confidence in the data and subsequent business decisions made?

I have known many supply chain companies who do make critical business decisions based off of spreadsheets.  For example, one company would use spreadsheets to analyze big order drop ins.  If they had a big order drop in they would use their spreadsheet(s) to determine the effect on their business and when they could commit to the customer to deliver the order.  This would typically require multiple spreadsheets getting data from multiple sources, tons of manipulation, trying to tie data together, and many different users from the organization looking at their piece, which would take several days and by then the data had changed and the end user would only have a 50% confidence level in the answer back to their customer.  This can be crippling if your products are very expensive like in the aerospace industry where the products are multi-million dollar and the customer is the government who may impose penalties if orders aren’t delivered when promised.

You need to:

• get all the supply chain data in one place for visibility (with frequent data refreshes),
• mimic the source system analytics,
• have all the system standard security functionality and
• output data in a familiar “Excel-like” format.

True nirvana is: one source of the truth, multiple users having access at the same time, data integrity, “what-if” capability with the power and flexibility of “Excel-like” outputs.