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There used to be a commercial (with Orson Welles for Paul Masson wines) on television back in the 1970’s advertising that they would “sell no wine before its time.” This implied that they wouldn’t release any wine until it reached full maturity and perfection. I thought this would be a good analogy for the concept of time phased release of supply orders to the supply chain. Shouldn’t we want to release orders only when they reach full maturity and perfection?

The temptation is usually there to release supply orders as far out into the planning horizon as possible so as to give suppliers more time to deliver. But what actually happens when we do that in an MRP planning environment? It artificially lengthens lead times, and consequently, we are releasing more supply orders into an already overloaded supply chain. It seems to me that we should build a recovery reschedule of the past due purchase orders and cut the lead times to the bone, only releasing new supply orders in the near term when the master production schedule is more mature and firm.

The APICS definition of Time Phasing is:

The technique of expressing future demand, supply and inventories by time period. Time phasing is one of the key elements of material requirements planning.

This definition to me appears to be overly simplistic and deserves further expansion into specific scenarios and benefits. The definition doesn’t say anything about the benefits of time phased release of supply orders in small bites. It should also include the benefits of time phasing the release of supply orders, based on precisely defined lead times in the near term, resulting in greater ‘maturity’ and ‘perfection’ of quantities and due dates.

I think the old adage, “How do you eat an elephant? One bite at a time,” applies here. The time phased releasing of supply orders at the latest possible release date that would satisfy the minimal lead time requirement would result in only releasing supply orders when the production schedule is firm. This enables better accuracy in release quantities and due dates, and less disruption in the master production schedule.

We can look at our entire planning horizon pictured above as a time phased funnel depicting firmed or released supply orders at lead time (dark shading), unreleased or planned supply orders (light shading), and gross demand and forecasts input and the resulting shipments to the customer. This planning horizon is funnel shaped because forecasts are generally more optimistic further out into the future and then start to lean out when approaching lead time due to forecast consumption by actual demand, capacity limitations of the master production schedule, and actual customer shipments.

If we take a closer look at the dark shaded area (firmed or released orders), we can probably say that a large portion of our planning horizon for customer delivery has, in effect, been relinquished to the mercy of our suppliers. So shouldn’t we want to limit that dark shaded area so that we can maintain as much control of our planning horizon as possible?

Another thing that can be said for this dark shaded area is that it is the labor intensive portion of your total planning horizon because of near term supply chain volatility.  Suppliers that can’t deliver, lack of capacity, acts of God such as the earthquake in Japan, all of these and more can contribute to near term fluctuations to your master production schedule,which result in overtime throughout the company in order to resolve the issues quickly.  Buyer/planners in particular, perform lots of work expediting and rescheduling released purchase orders. Despite the temptation to artificially increase lead times and therefore release more supply orders earlier, this can ultimately result in the buyer/planners increasing their own maintenance workload… sometimes beyond their means. Most buyer/planners I know are responsible for three or four thousand parts.

In the light shaded area (unreleased or planned orders), your suppliers have no control over your master production schedule. You do. In this area of the funnel, volatility, resulting in additional laborious tasks is not a problem. The MRP software handles it automatically. All planned orders are automatically rescheduled during every MRP run. So shouldn’t we want most of our time phased funnel to be light shaded? In this area, we can also favor and easily maintain the formal system over the informal system of order launch and expedite hotlists.

Think about this the next time an overloaded supplier asks you for more lead time to dig himself out of a backlogged hole. You just might be supplying him with a bigger shovel.

The first point they make is that for most companies, Excel is not a viable S&OP tool.

• Anyone who has done extensive work in Excel knows that it is a very powerful tool that works best with smaller data sets.  Companies managing a complex supply chain soon find that they are stretching Excel’s boundaries to the breaking point.
• Modern S&OP process have a significant “what-if” component to them.  While it is easy to make high level changes to Excel, understanding what the real impact of these changes are, is simply not possible.  Consider a typical S&OP decision…what-if we were to add a promotion for this product line? A simple question, but a complex answer.  Sure, you can change the forecast quantities in Excel, and that can show change to revenue.  But what-if the product line is constrained?  What is the purchasing spend going to be to support this?  A simple Excel model simply cannot support this level of granularity.
• Excel doesn’t support alerts or lend itself to managing by exception.  Once your S&OP plan is set, you need to monitor performance against it.  Sure, you can see how you’ve performed at the next S&OP meeting, but isn’t that too late?

I’ve gone into some details about how Excel is not the right tool for S&OP (and other things) in other posts, if you are interested, you can find them here;

Is Excel the right tool for S&OP
How are spreadsheets like cockroaches
The endless debate: Is S&OP about technology
When spreadsheets go bad

So, if Excel is not the right tool for S&OP, what is?  Rather than call out a specific tool, let’s look at some criteria that you need to consider when looking for an S&OP application:

• I mentioned that Excel is not a good tool for S&OP is because it doesn’t support “what-if” analysis.  This is obviously something you need to look for in any tool for long range planning.  But simply allowing you to hive off a version of the plan and make a change is not enough.  The “what-if” analysis must provide detailed analysis as to what the impact of a given change will be throughout the supply chain.  A key supplier of low level components was just hit by a flood and won’t be shipping parts for six months – what impact will this have on my production?  What-if demand increases on one of my product lines?  What impact does this have on a constrained resource?… on my contract manufacturers?… on my suppliers?  Only a system with full supply chain analytics can address these questions.

• A related requirement is integration.  If you are going to provide answers to the “what-if” questions above, you will likely need to have detailed information from multiple manufacturing centers around the world. These centers in all likelihood are running a variety of disparate ERP systems, so your tool will need to integrate across all these systems and bring the data in to a single environment.

• As mentioned earlier, the ability to monitor performance against the plan and report on exceptions is key.  A S&OP plan is good.  A S&OP plan that you monitor and react to when underperforming is truly powerful.

There are several other factors that can play into your selection of a system for S&OP, but I think these are key ones.   What tools are you using for S&OP planning?  Are you evaluating new tools?  What factors are you considering?  Comment back and let us know!

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.

Industrial activities, particularly those in lesser developed areas of the world, rely heavily upon the establishment and maintenance of the supply chain. For example, the first activity when drilling an oil well is the building of a road to the well site. These roads must be able to carry very heavy loads. In Talara, they relied on Caterpillar equipment shipped from the US. Downtime of this equipment was critical, as a one day delay in the completion of a well could have tens of thousands of dollars of negative affect on cash flow (With today’s crude prices, it might be millions of dollars). Any part or component that could be on the maintenance critical path had to be identified and its supply had to be appropriately managed. The difference 40 years ago was that inventories could be bigger and leadtimes were longer. Global competition in recent decades has driven the need for tighter budgets. There is constant pressure to be on time and on budget.

Dad spoke about critical path scheduling, which identifies those activities and resources that dictate and control the completion date. The paths have to be continuously monitored as they change, or as new problems/events take place. One key word here is ‘planned.’ Dad’s experience was that successful project management was based on testing the current plan with the question “what might go wrong” and then conducting reassessments where necessary. The most obvious insurance was to have spares for all the equipment and lots of surplus people to handle any eventuality. This was impractical and lacking the technological tools available today (there was a heavy reliance placed upon experienced personnel). Analysis was performed (pen and paper at that time!) on identifying the critical paths in the project plan, and actions were put in place to reduce their impact on project completion.

Some will argue against having a strong project management focus, using the argument that situations occur that you could never have planned for. When questioned about this, my father’s response was that these “surprise” events strengthen the argument for a strong, resilient planning system. Response Time is the key bottom line in emergencies and having a supply chain management system which uses project planning as a major tool can significantly reduce response time. (I had no idea that my dad was dealing with these responsibilities as I collected baby octopuses in the ocean, put them in a jar, and watched the water turn blue!)

Project management is required in numerous industries from refineries, to cell tower installations, solar farms, and consumer new product introductions. We agreed that it would be very beneficial if there was tighter integration of all dimensions of the project activity including materials, resources, cost projections, and revenue projections.

Thanks for the chat Dad. Ever since I was a kid I always wanted a fast car, an oil well, and an elephant. I have the first but I am not sure that the other two are very likely. At least I have a Dad who worked in the industry and helped me make an oil rig for my science project.

What we haven’t seen is apps that are directed at manufacturing and the supply chain…yet. I saw an article in Industry Week several days ago talking about mobile technology being used in manufacturing.  Two apps are discussed in the article; one is an app that allows sales representatives to view pictures and specifications of complex products.  The other is a plant floor app that can be used for material flow analysis.   These are interesting and in some cases necessary, but there is another area where mobile apps can be really exciting.

Let’s play a little scenario out in our minds; imagine the typical in-person sales meeting.  You are visiting with a prospective client trying to get orders placed for one of your high-profit products. Your customer is interested but they have an immediate need which requires delivery inside of lead time.  To add to the stress, they will place the order if you can confirm it today; otherwise they will place the order with a competitor.  So how do you respond in this situation?  The optimist (or perhaps the cynic) might say that you take the order and pray that you can deliver.  The pessimist might say that you don’t take the order and hope that you can do business next time (because you haven’t antagonized the customer by not delivering on a promise).  Either way, you are put in a difficult situation because you don’t have the information you need at hand.

Now let’s imagine the same scenario but this time you are carrying a tablet connected to your supply chain software. Using the tablet, you create a scenario (a safe environment where you can do “what-if” analysis without impacting actual production) and simply add your customer’s order. The analytics in the supply chain software evaluate the new order in the context of the existing customer orders, and the current supply, and capacity information and then determines an available date. It turns out that the available date (when the order can be shipped) is acceptable to the customer and you can accept the order with confidence. You are happy, the customer is happy, and your supply chain is happy because you haven’t promised something that may not be delivered.  This is where the true power of mobile computing shines for manufacturing and the supply chain.

Manufacturing apps are here.  Those that embrace these new capabilities will have a distinct advantage over those are stuck in the old paradigms. But the journey is only beginning; how do you see mobile applications changing your job? Comment back and let us know!

Aamer Rehman, vice president, manufacturing solutions here at Kinaxis, serves as the conference chairperson for Day 1 of the event, on January 26. As the chairperson, he will introduce each speaker, lead the Q&A after each session, and share his personal experiences and key highlights of the topics discussed. Aamer will also present the session “Continuous Sales & Operations Planning for the Manufacturing Sector” on Friday, January 27, at 11:30 am.

Here is the session abstract:

Planning has long been segmented into different isolated activities that reflect organizational structures and functional goals, leading to long, ineffective, and inefficient planning cycles. For maximized value, sales and operations planning (S&OP) must be a truly cross-functional activity that can directly and simultaneously address both individual departmental goals and joint corporate objectives. In this session, you will learn about the specific technology and process requirements to achieve a continuous and collaborative S&OP capability as it applies to the manufacturing industry in particular.

A recording of this session and slide deck will be made available shortly after the event. Stay tuned!

If you’re at the show, stop by booth #7 and say hi to the Kinaxis team! Also, make sure to follow the hashtag #SOPLVS on Twitter to get real-time updates from the event.

For more information on the Sales & Operations Planning Innovation Summit, visit: http://operations.theiegroup.com/sop-lasvegas

I got to thinking about this as an analogy for traditional supplier collaboration. Many manufacturing companies have implemented supplier collaboration solutions to pull in data in a more real-time fashion with suppliers. Traditionally, supplier collaboration involves the sharing of information between an OEM and a supplier related to component forecasts, purchase orders, Kanban signals and inventory positions. It’s important to share the information because of its direct impact on the ability to build product. And it’s important to share the information often because events in the supply chain can impact delivery schedules on a day-by-day and hour-by-hour basis. Many companies have implemented EDI (Electronic Data Interchange) and supplier portals to facilitate the systematic, high-frequency sharing of data. The unfortunate reality of traditional approaches to supplier collaboration is that the information that is collected goes into an information ‘dead-zone’ (i.e. ERP system) just like the mail stack. Sure, a buyer knows that a purchase order is going to be late but what is the impact of that? Buyers, on their own, typically don’t have the background nor the tools to understand the relative impact of exceptions (i.e. uncommitted forecast, purchase order receipt variance) on operations. How is a buyer supposed to know that an inability for a supplier to make a full commitment to a forecast could result in significant performance penalties on a large project, or that a partial delivery will mean a high-value order for a key customer will slip beyond a promise date?

What’s needed is the ability to collect the information and provide real-time impact determination and alerting to all roles in the organization including planners, customer service representatives, sales, project teams and executives so they can collaborate to solve problems while there is the opportunity to make a real difference to the business. This is the hallmark of the RapidResponse Control Tower and how using RapidResponse to support supplier collaboration initiatives can help you to achieve superior corporate and operations performance.

Today, time is on the cutting edge. The ways leading companies manage time – in production, in new product development and introduction, in sales and distribution – represent the most powerful new sources of competitive advantage.

Unfortunately Stalk decided to name the book he co-wrote on the topic as “Competing Against Time” which isn’t the point, although the subheading “How time-based competition is reshaping global markets” rescues the concept, which is really about competing against the competition with time.  It is all about being more agile, more responsive, to real conditions. Stalk sets out some Rules of Response very clearly:

• The .05 to 5 Rule
  Across a spectrum of businesses, the amount of time required to execute a service or to order, manufacture, and deliver a product is far less than the actual time the service or product spends in the value-delivery system
• The 3/3 Rule
  During the 95 to 99.95 percent of the time a product or service is not receiving value while in the value-delivery system, the product or service is waiting. (Stalk breaks this out into 3 components of waiting, hence the 3/3.) The amount of time lost is affected very little by working harder. But working smarter has tremendous impact.
• The 1/4-2-20 Rule
  For every quartering of the time interval required to provide a service or product, the productivity of labor and of working capital can often double. These productivity gains result in as much as a 20 percent reduction in costs.
• The 3 x 2 Rule
  Companies that cut the time consumption of their value-delivery systems turn the basis of competitive advantage to their favor. Growth rates of three times the industry average with two times the industry profit margins are exciting – and achievable – targets.

All too often though people get the impression that these rules are only applicable in the short term.  They are not.  The issue of responsiveness in operations is driven by the latency of the information and the time it takes to respond. In other words, the time to detect that something of significance has happened and the time to respond to the change, or correct the discrepancy. Reducing either of these will have a dramatic effect on a company’s competitiveness, whether this is a short term detection of demand change that requires rescheduling manufacturing or a longer term change in technology that requires the purchase of new manufacturing capacity.

Terms such as VUCA – Volatility, Uncertainty, Complexity, and Ambiguity – or PDCA – Plan, Do, Check, Act – don’t excite me because they are focused on removing volatility and complexity, usually promoting ‘stability’ at the cost of responsiveness, whereas Stalk’s concepts are all about being responsive, being agile. To me this is the correct emphasis. While of course there is an overlap in that a decision or manufacturing process that is overly complex will result in longer lead times, it is the overall sentiment of complexity and volatility being ‘bad’ expressed in VUCA and PDCA with which I disagree.  As I wrote in a previous blog from the 2011 Gartner Supply Chain Conference:

I say embrace VUCA. Accept that it is the new norm. Resistance is futile.

Similarly, Deming’s idea of PDCA is all about process improvement, it is about ‘managing’ complexity and ensuring ‘consistent’ processes. Again, I am not saying that these are bad approaches in and of themselves, only that they are insufficient.  Knowing that you are performing a process consistently doesn’t mean that you are performing it well.  It is like assuming that if you throw everyone in jail who has committed a crime that we will live in a crime-free environment.

Far more interesting to me is the OODA – Observe, Orient, Decide, Act – idea from the US military strategist Colonel John Boyd.

The steps of the OODA loop are:

• Observation: the collection of data by means of the senses
• Orientation: the analysis and synthesis of data to form one’s current mental perspective
• Decision: the determination of a course of action based on one’s current mental perspective
• Action: the physical playing-out of decisions

While at first this may seem to be very similar to VUCA and PDCA, the key point to the OODA loop is that:

Time is the dominant parameter. The pilot who goes through the OODA cycle in the shortest time prevails because his opponent is caught responding to situations that have already changed.

In other words reduce the time to detect and the time to respond.  To put this into supply chain speak, it is all about:

• Visibility – having access to the state of the supply chain across a wide span of operations, especially in outsourced environments, in order to detect misalignments
• Alerting – knowing or calculating the impact of misalignments on key financial and operational metrics in order to understand the severity of the issue
• “What-If” – working with others in the supply chain to come up with alternatives and evaluating these quickly
• Collaboration – to reach a consensus on the best course of action that reduces risk while increasing performance

Another absolutely key concept expressed by Boyd is the need for ‘human judgment’, for the system to act as an organic whole to adapt to situations as they unfold at the location at which they unfold.  Having long chains of command that force front line people to get approval from HQ is antithical to this idea:

… large organizations such as corporations, governments, or militaries possessed a hierarchy of OODA loops at tactical, grand-tactical (operational art), and strategic levels. In addition, he stated that most effective organizations have a highly decentralized chain of command that utilizes objective-driven orders, or directive control, rather than method-driven orders in order to harness the mental capacity and creative abilities of individual commanders at each level. In 2003, this power to the edge concept took the form of a DOD publication “Power to the Edge: Command…Control…in the Information Age” by Dr. David S. Alberts and Richard E. Hayes. Boyd argued that such a structure creates a flexible “organic whole” that is quicker to adapt to rapidly changing situations. He noted, however, that any such highly decentralized organization would necessitate a high degree of mutual trust and a common outlook that came from prior shared experiences. Headquarters needs to know that the troops are perfectly capable of forming a good plan for taking a specific objective, and the troops need to know that Headquarters does not direct them to achieve certain objectives without good reason.

These are key concepts we at Kinaxis have been promoting for a long time.  Every second that we waste in making a decision is a minute less that we have available to actually respond to situation.  In sports, reaction time is a well recognized competitive advantage.  Reaction time is coupled with the ability to ‘read the game’ and, for example, to call audibles at the line of scrimmage in American football. (I have always felt more comfortable with ‘European’ sports, such as soccer, that are a lot less structured and orchestrated precisely because the players have a lot more decision making power.) So in the end perhaps Stalk’s title “Competing Against Time” was correct, but this is a process efficiency perspective.  I still prefer the OODA concept of competing with time because this is about process effectiveness.

Vinnie mentions the fact that Daimler AG has over 1,000 developers in R&D, and a few hundred IT people supporting their internal enterprise systems such as SAP.  Of course they still have lots of people designing cars, but it is the amount of software that is in a car that is amazing. We are all aware of the more obvious innovations such as OnStar, which is developing into a platform like any other such as iPad or Android, with the recent announcement at CES of a developer community.

But it is the stuff ‘under the hood’ that is truly revolutionary, especially for the supply chain.  We are only getting there, but stuff is happening, especially in the industrial world. We are getting ‘smart’ machines that can self-diagnose, determine the corrective action, start a case, determine inventory availability, and schedule a technician to make a physical change when the material is available.  But now that so much software is imbedded in systems, this may require a software patch to be developed and downloaded when available.

Of course this is an extension of concepts first described 10-15 years ago when RFID first became available, even as long ago as when bar codes were becoming standard.  But these technologies could only really expand the use of inventory data.  I don’t mean to belittle the value of inventory data.  Far from it since ultimately it is the availability of inventory on a store shelf or in a warehouse that triggers the need for replenishment to satisfy demand.  But ‘smart’ machines go so much further.  In addition, naturally there will be analytic apps that absorb the information coming from many ‘smart’ machines in order to detect trends, for example that a certain mechanical part is failing more frequently or after a certain length of use.

Naturally the ‘smart’ machine scenario I paint above is most applicable to the service supply chain, but with the increased technology content in nearly everything that is man-made, the ability for a company to change how their product behaves by simply downloading new software is an incredible change for both the users and manufacturers/designers of the equipment.  I am old enough to remember washing machines and dishwashers that had electro-mechanical controllers for different cycles, and the mechanical systems themselves were often designed specifically for the cycles offered in that model. Now the mechanics are nearly identical, with different cycles being driven by software downloaded onto identical controllers.  I can see the day when we will upgrade our appliances by simply downloading new software, assuming the mechanics hold up and the aesthetics are still acceptable.  But why not have a ‘smart’ skin with selectable color and/or pattern that the user can change at any time?

But, while I agree with Vinnie that this is a major trend, at the same time, as illustrated by OnStar recruiting an independent apps development community, ‘smart’ machines should really be viewed as simply another user experience, such as tablets. In fact, I don’t see any reason why a tablet couldn’t be imbedded in a car’s dash, or a dishwasher’s front panel. So in the end I think many of the other trends are still very relevant, especially big data and cloud. But this is ‘structured’ data. The ‘smart’ machines will be programmed to issue clear and consistent instructions.

So where does social fit into the mix?  Andrew McAfee wrote an interesting blog in 2010 titled “Did Garry Kasparov Stumble Into a New Business Process Model?” in which he explores the trends of machine intelligence. Machines are very good at doing repetitive things quickly, including ‘smart’ machines. As McAfee notes,

Kasparov notes that computers play chess not by simulating human reasoning, but instead by comparing all possible moves and their consequences — the resulting board positions, subsequently available countermoves, possible counter-countermoves, etc. — until time runs out and a decision is necessary. And time will always run out; there are 10^40 possible legal board positions and 10^120 possible games, so even today’s fastest computers can’t be exhaustive. But they can be thorough, precise, and consistent. They evaluate lots of options, compare them rigorously, and never ever overlook or forget anything that they’ve been programmed to take into account

In other words machines, even ‘smart’ machines struggle to deal with nuance and ambiguity, though of course the recent experiment run by IBM in which they pitted Watson against top Jeopardy winners shows that even in this realm computers are beginning to gain ground. However, as stated by Greg Lindsay in his blog titled “How I Beat IBM’s Watson at Jeopardy (3 Times!)”, Watson is beatable by competing in areas in which humans excel, namely ambiguity and nuance.

Binary relationships–countries and their capitals, for instance–would be easy for him to figure out, and he would beat me to the buzz every time. So I had to steer him into categories full of what I called “semantic difficulty”–where the clues’ wordplay would trip him up. I would have to out think him.

So I am confident that in supply chains we will forever need human judgment and what computers will bring is primarily speed.  It will be in the exchange of unstructured data and the exploration of nuance and ambiguity that social will play its biggest role within the supply chain. After all, most decisions made between two supply chain partners are about compromise in which there isn’t one right answer, even though that is a view many supply chain vendors have promoted over the years through the use of optimization.

In conclusion, I agree with Vinnie that ‘smart’ machines and imbedded apps are big news and a major trend in IT and user experience. But from a supply chain perspective my sense is that ‘smart’ machines will mostly be an additional contributor to big data, which in itself is big news in the supply chain.  But it will be the manner in which we exploit social concepts in the supply chain that will be a real breakthrough because so much of supply chain management is about risk mitigation across a range of possibilities in a very ambiguous world.

Well, to jump to the punch line, the answer is likely “both” – depending on how one defines the terms.

A significant problem that exists in organizations today is that too many decisions get made without considerations of the impact on profitability or the feasibility of the decision given the impact that it will have on the employees in the organization.  There are numerous reasons why this is the case, but most of them come down to lack of integration –

• Integration between the processes within different departments, divisions and trading partners;
• People working within individual silo;
• Lack of integration within enterprise software products.

In this blog, I will stick to the last point, lack of integration within enterprise software products.  And … using the word “within” and not “between” is very deliberate.

Let’s first address the “distinct application” side of the answer.  The answer is a pragmatic one.  My firm belief is that distinct applications make sense if they are supporting distinct people and processes.  Financial statement reporting is an example of a profitability application that falls into this category.  The process is typically contained within finance, and it is a very specific process of reporting “closed” financial information to shareholders.

Where it makes no sense to have distinct products to handle issues such as profitability and human resource management is where these have a direct impact on decisions in business operations (so, basically in every business process).

By way of a real business example, if we reference the recent post by John Westerveld, it makes a ton of sense to integrate project management (product delivery) with supply chain.  But “how” do we assess the best possible scenarios to make changes?  We do it by taking in availability of materials (supply chain), availability of people (human resources) and deciding which option makes the most sense financially (profitability management).

In his post, John speaks of a scenario of installing a piece of medical equipment at a hospital where the equipment is going to be late and the power of putting the supply chain information in the project manager’s hands.  Let’s drill down on how this scenario would likely play out.  The project management would work with his equipment supplier.  They could evaluate the impact of the equipment being late and whether or not the supplier could still make the date if he found another supplier of the subcomponent which has become delayed.  What additional questions would they ask to determine if it would be worthwhile?

Will the delay cost us revenue?  Will any additional cost we incur be offset by the revenue gained? (profitability)

If the equipment comes on a different date, will contractors be available to install it?  Will it the inspector be available?  (human resource impacts)

If the financial (cost and revenue drivers) and human resource (rates, skills) information is only available in niche, departmental solutions, how can the company expect to make profitable and realistic decisions when projects don’t go according to plan?  Answer … they can’t.  Thus, integrated capabilities in a single application are needed for integrated planning, monitoring and response management.

In other words, profitability and human resource management are key to a Control Tower application.