Posts Tagged ‘Supply management’

Know Sooner. Act Faster. Not just a supply chain software conference theme

Published November 6th, 2013 by John Westerveld 0 Comments

We recently held our user conference, Kinexions, in Scottsdale Arizona. Attendees from around the world gathered to learn, laugh, share and connect. The event was kicked off by an address from Kinaxis CEO, Doug Colbeth. This was followed by an inspiring talk by Sir Ken Robinson discussing finding your passion: how you need to find what you love to do and then you’ll never have to work a day in your life. That was followed by several customer presentations describing how they’ve used RapidResponse to know sooner and act faster. And actually, that was the theme of the show…“Know sooner, act faster”.

If you are a Kinaxis customer, you know what this tagline means. For those who aren’t, this is what we are talking about:

Know sooner: Imagine that you have a supply chain disruption. Your supplier’s line has gone down and they’ve decommitted the next few weeks of orders while they make repairs and get caught up.   Imagine you found this out first thing Monday morning.  With your current ERP system, how long would it take you to understand what that delay would do to your production schedule?  What customer orders would be impacted?  What does this do to your weekly, monthly, quarterly revenue targets?  Maybe the supply delay really only impacts safety stock and minimally impacts actual customer orders. Perhaps the supply delay impacts millions of dollars of revenue.

Not knowing means either lost time working on minor problems (while more significant issues are ignored) or potentially not working a problem that could impact your company financially. Now, what if you had a system that would notify you when something like a supplier line down occurred.  Imagine if you could configure the system to only notify you if this change impacted customer revenue? Further, what if this system could lay out for you what the revenue impact was and the items causing these orders to be late. That is how you know sooner.

Act Faster:  Now imagine that the line down situation described above actually does drive millions of dollars of lost revenue? What would you need to do to recover? Do you find another supplier?  Can you substitute the late component with another equivalent component?  Can you offer customers a higher end product in place of the ones that are short? Or is it better to just accept that the late/lost revenue? Each of the possible resolutions have cost, revenue and customer service implications.

If you are using a traditional ERP system, you will need to pick one approach and go with it because you cannot effectively simulate different options, and even if you could, with the limited reporting capability inherent in today’s ERP systems, you can’t easily see the impact of those options on revenue, margin and customer service.  To act faster, you need to be able to identify those people affected by a change, collaborate with them to simulate the possible resolution options and then compare those resolution options  to see the revenue, margin and customer service impact.

When plans and events create risk/opportunity for you, the speed at which you bring together the right people to collaborate will make or break your operations performance.

It’s not difficult to see that knowing sooner and acting faster is a competitive advantage. Other factors being equal, reacting to changes in your supply chain faster than the competitions means that you will win more business, hold less inventory and earn more profits.






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

SupplyChainBrain Video Series Part 8: Celestica’s Supply Chain Collaboration Center

Published May 16th, 2013 by Melissa Clow 0 Comments

SupplyChainBrain attended our annual Kinexions user conference.

At our event they completed a number of video interviews with some customers, analysts, and Kinaxis executives. These videos are loaded with great information and we would like to share it with our readers.
Each week, we have been sharing the clips. The final video in our series is Celestica!

Celestica’s Supply Chain Collaboration Center

Celestica’s collaborative initiative comprises three elements – inventory visibility, much closer relations with suppliers, and optimized inventory management, says Erwin Hermans, vice president of supply chain solutions at the contract manufacturer. [Run Time (Min.): 12:22]


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Posted in Control tower, Demand management, Sales and operations planning (S&OP), Supply chain collaboration, Supply chain management, Supply chain risk management

Embrace Complexity – Revisited

Published April 17th, 2013 by Trevor Miles @milesahead 0 Comments

Tony Martins at Cyber Supply Chain published a very interesting blog over the weekend titled “The post-S&OP era – Managing in NOW mode” that explores the need and nature for more responsive and timely processes.

I agree very much with most of Tony’s perspective, but there are areas where I think the argument can be taken further, particularly in the understanding of the nature of the problem – which is complex – and the manner in which we can promote better resolution – through cross-functional collaboration. I very much encourage you to read Tony’s blog before continuing to read mine.

Tony’s Key Points

This whole thing is so 1990′s and yet so many people are still doing it. I’ve actually been in places that when I propose a completely different approach, I’m told “well that’s not proper supply chain management”.

Yes, I agree, and the reason being that people have defined an approach and processes to S&OP, and, more broadly, to Supply Chain Planning, based upon the technology that was available at the time these concepts were developed over 30 years ago. This required a reductionist approach of pulling the problem apart and focusing on functional skills such as demand planning, or inventory planning, etc. Nothing exemplifies this backward approach better than the 5 stage sequential S&OP process advocated by many experts in the field.

The problem is that the whole is greater than the sum of the parts, and an approach that starts from the perspective that the whole is the sum of the parts will never get us to a new level of capability and productivity.

 It’s almost as if a whole lot of people – senior Executives no less – believe that the world is on ‘pause’ while all this data is being processed. That, of course, isn’t the case and I am sure these Executives don’t think so either. And yet, they still think this is a good way to manage supply chains.

The essential issue is that people believe in ‘stability’, and that they can impose it on a supply chain.  As engineers – and most people in supply chain management today are engineers – we are taught to be deductive thinkers and our value is measured by how much we can pull apart a problem and devise an optimum solution. We feel threatened when we cannot reduce the problem to a set of known equations that can be solved and optimized.

The problem is that the world is messy (stochastic) and we have to make gross simplifying assumptions based upon very uncertain information – the demand forecast, and the supply forecast for that matter – so our optimum is not so optimal after all. In addition we way over-estimate the half-life of our (less than) optimal solution.

The core concept of NOW Management, as I call it, is that things change because specific disruptive events occur. If you made a plan, the plan continues to be good for a while until there is a disruptive event.

…, if Demand is changing, it can only be because of disruptive events – current events or future events.

You’ll have to allow me some disagreement.  It’s not that I disagree with the fact that there are disruptive events, but rather that I want to challenge the implicit assumption in Tony’s statement that the plan – both demand and supply – was correct in the first place.

Terra Technologies published a survey of demand planning capabilities in 2011 that focused principally on Consumer Goods companies, which, for obvious reasons, have always been at the forefront of demand planning.  The results of the study show that most companies achieve a weekly MAPE of 48%, meaning the forecast accuracy is only 52%. Anecdotal evidence from High-Tech suggests that the forecast error of supply lead time lag, is typically about 70% and Industrial companies cannot predict their forecast much better.

The problem is that since the supply plan aims to fulfill the demand plan, how optimal can the supply plan ever be? Not very is my answer. So the real issue is that as time progresses, we learn more and more about the true demand – which is not a disruption at all – and need to adjust very quickly to true demand.

As a consequence, my toes curl every time I hear that a company is using Plan Conformance as a KPI to measure the performance of their supply chain. Really?  The plan is ‘wrong’ and you are going to force your supply chain to deliver an incorrect plan?

Supply Chain Management in NOW mode can best be done (and I suggest that it can only be done) using social networking. I have written extensively about the power of Spontaneous Association to react to unexpected events at great speed, using the skills of qualified individuals in a dynamic, virtual network.

I mostly agree that it is the social aspect that is missing in our current deductive view of supply chain planning and management. I also agree very strongly that the only way to solve issues is through dynamic, virtual networks. Collaboration has been a hot topic, and much abused topic, for some time. More on this later.

And yet, it is not enough to let things happen spontaneously, as they do in the consumer world of social networks.  We need a little more control than that, but not a huge amount, that is based upon the concept of Responsibilities or ‘directed’ interactions. We definitely do not need something as rigid as a predefined business process orchestrated by a BPM tool. A much richer construct than social networks is Dynamic, Advanced, or Adaptive Case Management, which is implied, but not stated explicitly, in the process described by Tony to support NOW mode.

I’d like to suggest an alternative process that encapsulates the process he recommends.

  • Monitor the supply chain constantly to detect significant changes – which includes disruptive events – constantly based on predefined thresholds.
  • Direct an alert to the person responsible for the event and create a case file, what Tony calls posting.
  • Determine if the event has significant business impacts on other parts of the supply chain.
  • Direct alerts based upon the business impacts of the event to as many people as necessary notifying them of the case that has been opened.
  • Short term actions, governed by longer term operational and financial objectives, are identified and tested in what-if scenarios to determine the likely operational and financial impacts of these changes.
  • If the impacts of changes mean that other people need to be involved – which is determined through Responsibilities – they will be invited to participate in the case, while others who have filled their tasks may be pruned.
  • Then, other actions are taken to re-plan activities affected by the disruption.
  • From drawing up action plans, people naturally evolve to executing those actions until the situation stabilizes.
  • Since inevitably some trade-offs will need to be made between KPIs, a voting structure and approval process is required to govern the promotion of an action plan to execution.

Where Complexity Shines

In essence, if we adopt the process above, we end up with the Cynefin Framework combining aspect in the Known, Knowable, and Complex quadrants, with the express hope of avoiding the Chaos quadrant.


It is important to support several quadrants of the Cynefin Framework because, for example, process efficiency, and by implication cost reduction, is obtained through the adoption of standard best practice processes.  And contexts will change meaning new issues will arise, which we have not dealt with before meaning that the issues can no longer be dealt with adequately through best practices.  Equally over time we may gain insight through pattern recognition meaning we can adopt a best practice approach to solving this class of issues.

Another perspective of the Cynefin Framework is to look at the necessary capabilities required to deal with each of the quadrants.


This diagram illustrates very clearly why social concepts are so important, where standard Business Process Management approaches can be used to support the Simple quadrant, but are insufficient to support the more ad hoc approach required to support the Complicated and Complex quadrants.

Yet another perspective of the Cynefin Framework highlights both the skills and capabilities required to deal with each of the quadrants as well as the role of Best, Good, Emergent, and Novel practice within the quadrants.

Unfortunately, we tend to adopt the practices of the bottom two quadrants – Chaotic and Simple – when in fact most of our supply chains operate in the top two quadrants – Complex and Complicated.

We tend to consider that all issues can be reduced to best practices when in fact the exact conditions that direct our actions – both cause and effect – are almost never repeated. Best practice is indeed suitable for the usual and mundane events, but then these are unlikely to require much attention. All too often we force significant events to be dealt with through Best Practice thereby both overestimating the benefits and underestimating the risks. Commoditization and a slow death lie in wait in the Simple quadrant.

All too often people in the front line wizen up the impracticality and inappropriateness of Best practices in dealing with real world issues, and in the absence of any supportive infrastructure gravitate to the Novel quadrant where ‘seat of the pants’ approaches dominate. Clearly this is not sustainable either because costs go up or quality goes down.

The question is how we gravitate to the top left Complex quadrant. But, before discussing that in too much detail I also want to deal with the issue of complexity.  Some time back I commented on a blog entitled “Embrace Complexity” that describes a Harvard Business Review devoted to Complexity Science. Some colleagues have expressed their concern that I seem to be promoting complexity. Well, not really. In fact quite the opposite is true.

What I do believe is that a supply chain is a very complex network that cannot be disaggregated into a set of functional silos in which best practices are applied without context and acknowledgement of the interconnectivity between functions. In other words, the whole is much greater than the sum of the parts and therefore reducing everything to best practice robs the organization of vibrancy and change, or adaptation to meet new business opportunities and challenges. In other words I start from the idea that a supply chain is a complex web to which we need to bring simplicity by focusing on what is important rather than through simplifying and therefore robbing the supply chain of the richness of the network of interactions.

My favorite diagram in this context that captures the duality of simplicity and complexity is below.

This is where we have a lot to learn from Generation Y on the use of social networking concepts in an enterprise world. It is not as simple as providing an unstructured social platform.  There needs to be sufficient structure to promote timely resolution of issues and sufficient lack of structure to promote ad hoc and creative solutions to issues that transcend a single function.

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Posted in Control tower, Milesahead, Response Management, Sales and operations planning (S&OP), Supply chain collaboration

Is Microsoft missing the mark – or should I say, market – again?

Published November 2nd, 2012 by Kirk Munroe 1 Comment

Windows 8 is here and the Surface tablet is shipping. Is this going to put excitement back into Microsoft or just fall with the thud of Windows 7 phones, Zune, and some many other launches of the past ten years?

Is Microsoft missing the mark – or should I say, market – again?

Just over 12 years ago, literally at the turn of the century, Microsoft was still a massively dominant software company. Windows-based personal computers accounted for 95% of the market (vs 30-32% or so today) and Microsoft still had the uncanny ability of picking – and then quickly dominating – new market areas. (Whether or not Microsoft was a great innovator remains a topic of great debate, however, it is hard to question their ability to pick and dominate markets).

Since 2000, Microsoft has certainly done OK – especially compared to many other high flying software companies of the time – but they have also haven’t done anything exciting over that time either. A dollar investing in Microsoft stock 10 years ago today would be worth $1.06 (unless you are Canadian and it is worth about $0.68 with exchange, sigh). Google was obviously a new company, but a dollar invested 10 years ago would be worth $525 today and a dollar in Apple would be worth $7800. Let’s face it, over a 10 year period, stock price is a decent proxy for success.

So … what went wrong and are they repeating it again?

Microsoft flat out stopped going after new markets, or probably more accurately, they stopped their efforts at dominating new markets created by others early in the emergence of those markets. Basically, they have been late to market with everything. In Geoffrey Moore speak, usually both the gorilla AND chimps were already established before Microsoft entered the game.

With Surface and Windows 8 (and the inevitable MS Surface phone), is this game playing itself out again? It sure looks like it. Apple and Google (plus the Google-Samsumg partnership) are dominating the smartphone market in the personal productivity market, with RIM hanging on as a third player for the business-centric buyer (and to a lesser degree in the personal market). Microsoft currently, with about a 4% share, is nothing more than a rounding error.

Does it need to be this way?

No way! Is we step back from all the feature debates and religion around open vs closed platforms, there still is a market to grab. Especially since this “market” turns over at a rate unheard of in history.

Let’s look at what made Apple so great so quick – cutting through all the feature/religion garbage and getting back to core principles. When the iPhone and then iPad came out, they made people’s lives a lot more productive – after all productivity is the only reason to adopt technology in the first place. (I would even extend this to gaming and movies – making our “recreation” time more productive is what wins in this space too.) I admit it. I bought the original iPad the day it came out. It has made my personal life more productive. Picking meals, to grocery shopping, to cooking is easier – no more looking through books, writing out lists and digging books back out! I love sitting on the sofa watching TV and going, “That actor looks familiar.” Quick to the iPad, IMDB, voila! Would I have pulled out a laptop to satisfy that curiosity? … unlikely.

However, has Apple (or insert Google-Android here) made my work life more productive? Not a lot. It is easier to travel with music, search the web, get email and calendar (barely), and so on. It is barely “good enough.”

A lot of you might be like me and still spend a depressing amount of time in PowerPoint, Excel, Word, and Outlook. Has iPhone/iPad and Android helped here? Not really. (If you answered “yes”, you are either kidding yourself or have a much lower standard for convenience that I do!)

Imagine in the late afternoon when I have to run to see a basketball or hockey game … no more rushing to save work and pack up a laptop. Grab my Surface device and pick up mid-PowerPoint when I get home (or mid-email, Excel model, etc).

Basically, I am saying that Apple/Android has gone to market with a “Great for Personal. (Barely) Good Enough for Business.” model. Microsoft, why can’t you take a “Great for Business. Good Enough for Personal.” approach. I would buy that!

I am hopeful, I just don’t think they can.

The single biggest indicator is the new Windows 8 ads. Who thought it would be a good idea to go to the ad agency and say, “We are going to dedicate ¼ of the money and 1/10 of the time Apple thinks about advertising and go-to-market, but please copy their ads!”?

Thirty seconds of confusing people. Great job.

Please, Microsoft, try to make this interesting. Apple vs Android just isn’t fun anymore.

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Posted in Demand management, Supply chain collaboration, Supply chain management, Supply chain risk management

Another One Bites the Dust: RedPrairie

Published November 1st, 2012 by Trevor Miles @milesahead 1 Comment

Another One Bites the Dust: RedPrairie

It is with great surprise that I read about the demise of yet another company focused on supply chain planning, namely the purchase of JDA by RedPrairie for $1.9B.

Of course RedPrairie does not see it in this manner.  They see this as growth, as opportunity.  Equally interesting is that it is RedPrairie, with revenues of about $300M, that has bought JDA with revenues of close to $700M. I can’t help wonder how that came about.  Of course it could be a lot more innocent.

More important is the fact that JDA has been formed through the acquisition of a number of other supply chain companies, most notably Manugistics and i2 Technologies, both pioneers in the supply chain planning space.  JDA was already struggling with rationalizing the number of software applications to reduce the cost of maintenance and bug fixes, and now RedPrairie will need to evaluate how to absorb the JDA applications. Lest we forget i2 Technologies also grew through acquisition of Think Systems, OptiMax, ITLS, Aspect, and Smart Technologies, amongst others.  So did Manugistics. And then JDA. And now RedPrairie. Same DNA, same result?

Of course roll-up is the same business model adopted by Infor. Perhaps this is the route RedPrairie, or, more correctly, New Mountain Capital, RedPrairie’s owners, has chosen. Here is the list of Infor acquisitions in Wikipedia, and I don’t even seen BaaN on this list. (The accuracy of Wikipedia is a whole other topic I won’t get into here!)

Infor Acquisitions

  • Agilisys (SCT) (2002)
  • Brain AG (2002)
  • Future Three (2003)[5]
  • Infor Business Solutions (2004)
  • Daly.commerce (2004)[6]
  • Varial Software (2004)
  • NxTrend Technology (2004)
  • Aperum (2004)
  • IncoDev Software (2004)
  • Lilly Software Associates (2004) [7]
  • Mercia Software (2005)
  • MAPICS (2005)
  • Paragon (2005)
  • Intuita Holdings (2005)
  • Alpine Systems (2005)
  • Formation Systems, Inc. (2005)
  • Datastream (2006)
  • GEAC ERP (2006)[8]
  • Extensity (2006)
  • Systems Union (2006)
  • SSA Global (2006)
  • Profuse (2007)
  • Workbrain (2007)
  • Hansen (2007)
  • Corpsoft (2007)
  • SLA Management Services (2008)
  • SoftBrands (2009)
  • Bridgelogix (2010)[9]
  • Qurius (2010)[10]
  • Hotel PMS division of Amadeus IT Group SA
  • Lawson Software (2011)
  • ENXSUITE (2011)
  • Easy RMS (2012)

Having been around in the early days of i2 Technologies, when they only had one product, Factory Planner, I have mixed emotions.  There is a lot that i2 Technologies, and Manugistics, brought to the table.  They changed the way we saw the problem; how we went about planning complex supply chain planning problems.  I am very proud of the time I spent at i2.

But there was always a major flaw in the approach of the early vendors to supply chain management as a practice.  They approached supply chain planning by addressing the needs of individual functions without giving any thought to the value of cross-functional process enablement. What they ended up with was a Rubik’s Cube of solutions.  I was at a two day conference held by the Center for Transportation and Logistics at MIT recently during which one of the participants said that they have over 200 supply chain management applications, which means that when implementing new functionality the cost of integration is greater than the cost of purchase and deployment of the new application. That is a sad state of affairs.  How are they going to innovate in that environment? But we were all – vendors, practitioners, analysts, academics – complicit in segmenting supply chain management into functional silos, divorcing demand planning from supply planning and materials planning, divorcing new product introduction from procurement and capacity management, divorcing trade promotion planning from supply allocation and distribution requirements planning.

The ERP vendors are faced with the same issues. Oracle has grown its application suite through acquisition, most notably Demantra and JD Edwards. While SAP has grown its APO suite through organic development, they too have followed the functional silo model with 7 individual APO modules with different data models, code bases, UIs, and analytics engines.  How are we ever going to be able to support horizontal cross-functional processes and even multi-enterprise commerce with these architectures? Of course Oracle has tried for several years to solve this issue with Fusion and SAP with NetWeaver. Following either of these links is to be faced with yet another list of modules and components required for Fusion or NetWeaver. And Infor has ION, i2 had Agile Business Process Platform, and RedPrairie has E2e, all of which try to accomplish the impossible. This issue of multiple functional solutions also impacts innovation in the supply chain space. With vendors so focused on integration between modules, where is the process innovation going to come from? With small groups focused on functional needs, where is the cross-functional innovation going to come from?

From attending multiple conferences and working with big customers I hear a lot about the need for horizontal process enablement and innovation.  Of course any of us can still find conferences that focus on functional excellence, and I’m not suggesting that functional excellence is not important.  The gap, though, what is missing, is the horizontal, cross-functional process enablement.  This is why there is such as buzz about what we call Supply Chain Control Towers or, what Jim Shepherd called “Multi-Enterprise Commerce” while he was at Gartner.  Unfortunately Jim’s original post on Gartner’s First Things Monday blog is no longer available, but here is what he said on Supply Chain Brain.

The real business problem that today’s manufacturers and distributors are struggling to manage takes place between companies, not within them. Planning, sourcing, production, costing, tracking and fulfillment must take place in an environment that can be accessed and updated by all the players in the value chain. This certainly suggests cloud-based services, rather than a series of on-premise systems hidden behind various firewalls. The applications themselves will also have to be redesigned to accommodate rapidly evolving supply networks and extremely fluid material ownership.

Application designers could learn a lot from today’s Web store, lsupply chain and sourcing products, but they need to extend the scope to include finance, asset management, traceability, order management and service. In a multi-enterprise environment, these activities will need all new business processes, and the expectations for control, visibility, and efficiency will be quite different.

I can envision this “multi-enterprise commerce” suite, and I can see how valuable it would be for companies in industries like electronics, life sciences, food and beverage, or fashion. Their businesses today are really based on creating and managing global value chains that may have dozens or hundreds of participating entities. I don’t think the fundamental design of ERP fits this business model very well, and I don’t think just moving it to the cloud really solves the problem.

I agree with Jim’s assertion that manufacturers are struggling to manage what takes place between companies, but I am not yet convinced that they have satisfied the need for horizontal or cross-functional processes within them. Because of outsourcing, what has happened over the past two decades is that many of the internal functions have been outsourced, validating Jim’s statement.

I was asked to comment on the merger by fellow blogger Jason Busch from Spend Matters. He shares some interesting perspectives on this industry news – you can read the article here.

So we live in interesting times.  I can’t wait to belt out that other perennial Queen favorite. Know the one I mean?

Posted in Control tower, Demand management, On-demand (SaaS), Supply chain collaboration, Supply chain management, Supply chain risk management

Reflections on Kinexions 2012

Published October 25th, 2012 by Kirk Munroe 0 Comments

We had our annual user conference last week. All early signs point to Kinexions ’12 being a great event. The feedback from customers and the influencer community has been 100% positive (fingers crossed for future blog posts!).

Reflections on Kinexions 2012

The conference was my second since joining in August of 2011. As the conference was wrapping up, it really made me reflect on why I joined the company in the first place and why I continue to love working here.

Back on August 28, 2011, the day before I joined, I wrote a blog post on Why I am Joining Kinaxis. The three main reasons were: (1) the technology and approach behind RapidResponse, (2) happy customers and (3) the Kinaxis team. I loved what I saw of my interactions with employees. I was blown away by the case studies and customer stories. The product was something I had been waiting to see since I started my software journey as a product manager many years ago. Well, after my second Kinexions, let’s take stock on where these sit today.

Kinaxis Team

We use LLSC to mean both “Late Late Supply Chain” Show and Learn, Laugh, Share and Connect. Let’s face it – Supply Chain is hard. It is even harder than I thought a year ago. Promising orders, reducing inventories, collapsing cycle times, reducing planning cycles, gaining consensus on demand forecasts – these are not fun. So, the fact that we can get supply chain people together to laugh (a lot!), share their experiences, learn from experts and each other and connect with their peers – to collaborate around solutions to these complex problems in a relaxed setting – is really important and something that is at the very core of our culture. Hopefully, we will be able to post some videos of the event shortly to make this point (for those of you who were not there).

Verdict: Exceeds my initial expectation

RapidResponse Technology and Approach

RapidResponse is also better than I expected. Although I am not surprised about the power of one product – a single code based to solve many business challenges – I am surprised at our ability to innovate on top of the platform. Working in – and competing against – many other enterprise software vendors, it always seemed that the only path to new innovation was through releasing new products. Old products become “legacy” quickly because they are not built with a view to the future. The mantra of innovation in software companies is “new problem: new product” (where “new product” often means “acquire a small innovative software company”). So, naturally, I was skeptical about our ability to get new innovations to market in a timely fashion – we clearly were not going to compromise on having a single product. Well, all my worrying was needless. In calendar 2012, we will have had three releases (11.0 in March, 11.1 in July in 11.2 in December) bringing the following innovations to market (just as examples of a larger pool):

  • Database namespaces – to extend RapidResponse into new application areas
  • Non-Blocking Allocations and Multi-Level Sourcing – to free up material resources to get products to market quicker (without compromising delivery of other products)
  • Workbook and Alerting Enhancements – to allow for more rapid application development and reuse of resources (usability)
  • New demand planning analytics and chart types
  • Mobile offering – auto-creation of dashboards in HTML5 to be device independent for highest adoption (ROI) and lowest maintenance (TCO)
  • Integrated project management – to balance supply and demand of both material and human resources (filling a major hole in the market)
  • Real-time Data Integration – through the inclusive of an enterprise service bus and queuing service embedded into RapidResponse
  • Attribute-based planning – for analytics extensions and flexibility in planning
  • Feature (or variant) bill of materials – for companies doing configure-to-order off a feature list
  • New scripting engine – for customer-based extension of workflow and automation
  • Process orchestration – to co-ordinate planning and response activities
  • New S&OP resources – including a calendar-based view of S&OP ownership by date

Verdict: Significantly exceeds my initial expectation

Happy Customers

I can start with the verdict on this one. It is seriously way above what I could have imagined. This is not hyperbole at all. I have also rewritten history and moved this up to #1 on my list – in spite of being a product guy who found a product that easily exceeds my expectations, this one is more important, refreshing and frankly, unbelievable in spite of seeing it numerous times now. Let’s face it, happy enterprise software companies is an oxymoron to most people. Not to say that some of our customers don’t have challenges with the software some days – of course they do. BUT … instead of me going on, I suggest that if you are reading this and were not at the event last week, that you should check out the recordings by Laura Dionne, Guenter Schmidt, and JP Swanson of TriQuint and Don Gaspari of NCR. Not only do they share our values of learn, laugh and share in these presentations, their stories talk about very transformation initiatives that they have achieved with RapidResponse. If you have the chance to watch these, take into consideration that no one from Kinaxis saw (or asked to see) these presentations before the conference. They are completely the unedited work of the authors. We also had great presentations from Shellie Molina of First Solar at our influencer event, Lieu Yoke Sun from Agilent and Erwin Hermans from Celestica.

Net/net: Things are going really well at Kinaxis.

Before I close, I also want to pass on my favorite tweet (and there were a lot of good ones) from the conference tweet stream #kinexions12 and #kinexions. I really like this one because we really feel that we are the “ of SCM” or the “Workday of SCM” but we never talk to the market that way.

This one was all Frank Scavo (of Constellation)



Posted in Control tower, Supply chain collaboration, Supply chain management, Supply chain risk management

Dude, Where’s my car?

Published October 10th, 2012 by Andrew Bell 0 Comments

Dude, Where’s my car?

I recently had the opportunity to attended the Automotive Logistics Global conference in the Motor City, Detroit Michigan. As a self-proclaimed “car guy”, the conference proved to be a fascinating behind the scenes look at the logistics of turning raw materials into the beautiful finished good we call the modern automobile. I had no idea about the complexities of the logistics involved and the amount of product that needs to be produced, manufactured, shipped and tracked all over the world.

Before I share some of the conclusions I took away from the subjects that were discussed, I must admit that I’m borrowing the idea for the title of my blog post from one of the sessions at the conference that was titled “Dude, there’s my car”. I think that either title (where or there) makes reference to an important challenge that the automotive logistics industry faces. Visibility. There a number of areas within this industry  where visibility plays an incredibly important role, ranging from the visibility of the market (supply and demand) of raw materials to visibility into the availability and delivery date of finished vehicles to dealer lots.

There is no doubt, and it was definitely emphasized in various forums at the conference, that while visibility is key, it’s also a challenge. With realities of lean manufacturing and just-in-time (JIT) delivery, one key area of visibility for an OEM is that of the shipments of parts that are destined for it’s plants. One example of some successes in this area was shared during a joint presentation by Matt Jorgensen from Ford and Kevin Denomme from Penske. Leveraging GPS technology on it’s fleet of trucks and the transfer of this information via Electronic Data Interchange (EDI), Penske had been able to provide Ford increased visibility into the arrival time of key components to it’s plants. This has obviously assisted Ford in getting their plants to be more efficient and prevent downtime due to late deliveries. However in  the complex industry that is the automotive manufacturing industry, an OEM having visibility into the delivery time of parts to it’s facility is just the tip of the iceberg. There are multiple tiers of suppliers, all the way down to the raw materials, as well as the transportation of goods between all these tiers that make getting visibility into the entire supply chain a huge challenge.  It’s clear from the discussions that were held at the conference that the more visibility that can be gained into this supply chain, the more efficient and profitable the whole industry can be.

The idea sounds seems simple enough. Provide more visibility throughout the supply chain so that we can all be more efficient and profitable. But what was also clear is that all this visibility also mean a lot more data. And thus another challenge arises. What do I do with all this data? How do I store it, manage it, not to mention, make decisions based on it

From what I could tell, all this added visibility and the data that comes along with it could be one of the next big challenges for the industry. It’s not good enough just to collect the data but not act on the data.

The better a company gets at analyzing that data, the more gains that company can make in terms of quickly detecting issues, and taking action earlier to mitigate issues. Essentially, knowing sooner and acting faster.

With all this data, there is no doubt that sophisticated tools are required to put the data to best use. These tools need to provide decision makers with the ability to do key things:

1)      Visualizations and Alerting – It’s critical that decision makers can get clear visualizations of the data in order to see what is happening in the business (through dashboards, charting etc..). The addition of alerting capabilities to this provides early detection of situations which are trending in the wrong direction.

2)      Scenario creation – it is one thing to identify a problem, but it’s another to analyze all the potential solutions. Having the ability to run and compare multiple what-if scenarios is key to being able to determine the right action in order to manage and mitigate the issue.

3)      Fast Analytics – Doing all the above at lightning speed. Decision quality can’t come at the cost of decision speed. It’s critical that the financial and operational impact of the issue and the solution being considered be calculated instantly.

By the end of conference, it was clear that the industry is making great strides at improving the visibility into the supply chain. The answer to the question, “Dude where’s my car?” is becoming easier and easier to provide. But the next step, and the step that I believe will yield even greater results is to not only answer the question, “Dude where’s my car?” Instead, we need to be able to say “Not only do I know where your car is, but I’m making informed decisions to get it to you faster and with better productivity and profitability for the business!”


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

Real Option Analysis is relevant to Supply Chains too

Published July 13th, 2012 by Trevor Miles @milesahead 0 Comments

I want to bring together a number of thoughts in this blog, most importantly the idea that as the practice of supply chain management has aged, there is a more rounded approach to the education and training of people entering the practice. Lora Cecere’s view is that we are entering the 3rd generation. I hope so because, by Lora’s definition, I am 2nd generation and I had a far too narrow education. Perhaps this was more a reflection of my choices than what was available, but I did take English, History of Art, German, and Philosophy as electives during undergrad and grad school. But I never took Finance or Accounting. I could have taken some Biz Studies courses, but I thought these were way too applied. I wanted ‘hard science’; things with differential equations and mathematical optimization. There was a Finance in Engineering course that was considered an easy option, but there were very few girls who took the course. Oh well, that wasn’t the only mistake I made in the past that was based more on testosterone than an understanding of skills or knowledge I needed to acquire.

supply chains

Over the years, I have come to understand and appreciate the importance of financial outcomes, but I was well into my 30’s before I could read a financial statement. In truth, it was probably a few years after that before I understood what lay behind a financial statement. And being self-taught, I have no doubt that there is much I still do not understand. But I would still rate my knowledge to be well above average amongst the self-taught supply chain community that studied one form or another of engineering or computer science. And that is a pity.

But this blog isn’t about education for supply chain or finance for engineers. It is about how one narrow aspect of financial analysis taught me to view supply chain decisions differently, Real Options Analysis.

As I have commented in the past (I am adamant that an accurate forecast does not reduce demand volatility), a tipping point in my life was when I understood the effect uncertainty or randomness has on our ability to analyze a situation with any degree of precision. I have come to the conclusion that other than for high-level network design or very detailed production planning/sequencing, optimization techniques have a limited application in supply chain management. I had got to this point because:

  • There is very limited capability to represent uncertainty in linear programming (LP, IP, or MILP), or there was in the early 1980’s when I was studying this stuff
    • Nearly all variables, such as lead time, throughput, and demand have some level of uncertainty to them, often quite a lot
  • I had come to realize that these techniques force you to linearize highly non-linear systems, such as manufacturing or supply chains
    • Which is adding approximation to uncertainty
  • All optimization techniques force you to select some common unit-of-measure, usually money, for the objective function
    • This necessitates the development of ‘factors’ to convert operational measures, such as customer service, into a currency, when this relationship is not proven, known, linear, or static

white mountains

As part of my graduate research I had come to the conclusion that I had to use some modeling tool that allowed me to incorporate uncertainty and that also did not force me to linearize the system I was modeling, which made me investigate discrete-event simulation tools. From an optimization perspective I had to adopt pattern search techniques, such as Hooke-Jeeves. I was familiar with both non-linear systems and search techniques from my Chem Eng background but this was a whole new world for the Industrial Engineering department, while the IE department knew a lot more about uncertainty than I did as a Chem Eng. There was some vigorous discussion with my committee and advisor because the purists did not see search techniques as real optimization. The pivotal point was when I convinced them that if the model is not sufficiently accurate you can’t prove that you have found the optimum – max or min – anyway. They reluctantly allowed me to continue with my ‘practical’ research as opposed to a more theoretical approach, because at the heart of my research was the understanding of risk, which I thought was a novel approach at the time.

Once I managed to hook up the discrete-event model with the optimization technique it was taking over 40 hours to run an optimization of a fairly simple manufacturing cell with 5 machines, 3 operators, and 50 SKUs. Obviously this was way too long for practical use. That didn’t matter in academia, but it did matter to me, and it did matter to the manufacturing company with whom I was working. From an academic perspective, the interesting outcome was that the shape of the result was like a bath tub. In other words, there was a huge area where you couldn’t tell with 80% confidence where the true optimum lay, which meant you could select a wide range of values for the input variables without having a measurable effect on the result. Using a 95% confidence level only makes the bottom of the bath tub even wider. I then investigated the effect the degree of uncertainty/randomness of the input variables had on the shape of the objective function. Unfortunately it was more than 1:1 and it was not linear. Even if I made all but one input variable fixed – I chose to keep production rate variable – the degree of uncertainty in the objective function was greater than the degree of variability of the input variable, and as the variability increased the degree of uncertainty went up faster.

Using the analogy of a bath tub implies that there are only 2 input variables when in fact there are many. In a multi-tier supply chains there are thousands.

As an example of real-world variability, at a recent supply chain conference someone from one of the leading CPG companies said that their monthly demand Coefficient-of-Variation (CoV = std. dev./mean) for many of their high revenue items is over 1.5, largely because of the effects of seasonality coupled with promotions. He said if anyone in Operations thinks that either seasonality or promotion planning is going to decrease they are delusional. CoV should not be confused with forecast accuracy, but higher CoV usually results in lower forecast accuracy. And a CoV of 1.5 is very high. But a CoV of 3 is not unusual for NPI. So even if we have a perfectly accurate model of our supply chain, how optimal will be the supply plan? This was the problem I was trying to address in my research.

SCM diagram
I was still forced to use an objective function, despite all the drawbacks this implies. I wish I had known then what I know now about accounting because I would have tried to use something like Return-on-Assets (ROA) as the objective function. But the issue with something like ROA is that it is affected by the cost accounting method used. (By the way, I am certain that there is at least one Finance or Accounting person out there whose toes are curling while reading my simplistic explanation.) The objective function for a fixed cost allocation method will give very different results from a variable cost method. But at least it would be consistent with the company’s financial accounting methods, and understood by Finance. Instead, most objective functions are only understandable by the team that wrote the original optimization and therefore is not changed – because it takes too long to change – as market conditions and/or company objectives changes. Actually, I question whether the objective functions developed by Operations people ever matched the company’s financial objectives.

I have come to adopt Warren Buffet’s (amongst others) mantra, namely that it is better to be approximately right than precisely wrong. I believe much more in being directionally correct.

So how can we use this to make everyday decision in the supply chain? One of the most common forms of analyzing the future value of an investment is Discounted Cash Flow (DCF). Of course any decision we make in supply chain planning is an investment decision, even though our decisions are not usually viewed from this perspective. The reality is that in planning we are choosing to invest

  • cash in materials we buy,
  • productive capacity in the converting the materials we buy into items we sell,
  • people in managing the supply chain, and
  • sales and promotion funds in getting the product into customers hands.

DCF is usually used to analyze capital investments, not operational investments. All our decisions should be evaluated using DCF. But DCF has a fundamental flaw, namely that it is the analysis of the most probable outcome, and I have just spent a page explaining that the market is highly variable and uncertain. So how do we understand the most probable outcome?

I have come to see Real Options Analysis as a better form of analysis than optimization, because it incorporate the concepts of uncertainty and likelihood. Here are some links to videos on YouTube: Link 1, Link 2. But a fundamental flaw in Real Options Analysis is that it assumes that you know the probability of an outcome before the fact, for example how well a product will be adopted in the market. If we did know outcomes before the fact we would all be rich. More importantly, the first video outlines the need for continuous adjustment of a plan – whether long term, medium term, or short term – as we gain more information. In the first video, the speaker refers to this as Monte Carlo simulation, which is really just a way of automating what-if analysis. In fact, the third video points to a decision tree, which is essentially a what-if analysis of scenarios and outcomes. This is where human judgment or experience comes in. There is still – more correctly there should still be – a place for human judgment in our decision making processes precisely because of the uncertainty.

Scenario analysis, or what-if analysis, is a key capability in which people can perform an analysis of the likely outcome of a set of choices or decisions. Human judgment can be applied to evaluating the likelihood of achieving the outcome, in other words the risks associated with an outcome. But without the ability to evaluate different options quickly across multiple metrics – both financial and operational – it is difficult for a team to arrive at a conclusion of the best way forward that balances opportunity with risk.

Lastly, I just want to go back to a key point about Real Options Analysis, namely the continual reevaluation of the options as more market information is received. If we bring the concepts together they add up to Know Sooner; Act Faster.

Posted in Best practices, Milesahead, Sales and operations planning (S&OP), Supply chain collaboration, Supply chain management