Category Archives: Market Intelligence

What the Heck is a Supplier SuperCycle?

A recent post over on Procurement Leaders chronicled the results of July’s Procurement Intentions Index graphs that record changes in CPO strategy intentions over time, based on a survey of their CPO panel. According to the post, their results show the clear intention of CPOs to consolidate their supply chains by reducing the number of suppliers they work with, while, at the same time, spending more time collaborating with those that remain.

Based on these results, the author believes that the supplier collaboration and consolidation results are part of a “super-cycle” and that we will see the Index positions of both of these remain broadly the same for months if not years to come. That is until future CPOs believe they have reached the perfect number of suppliers and want to increase price competitiveness by taking more on board.

I don’t get it. I do agree that a subset of Supply Management organizations will be focussed on supply base consolidation and that a further subset of these will be focussed on collaboration in the hopes of mutual innovation, but I don’t think this is a super-cycle. A supercycle is a long period, or wave, in the growth of a market, as described by the Elliott Wave Principle. By definition, a super-cycle has to be market wide, and include all Supply Management organizations in all stages of maturity, not just the ones that are smart enough to be involved with a leading Procurement organization and respond to their surveys. While I do think that this is a mini-cycle in the above-average supply management organizations moving towards best-in-class status, most below-average organizations are still focussed on cost-reduction at any cost (to justify further investments in technology and transitions to better processes), and this typically involves auctions and negotiations that open up the procurement process to new bidders in hopes of getting more-cost effective, or higher-quality suppliers, for the organization.

This does mean that, as some organizations advance up the maturity curve, the mini-cycle will repeat, but then, as the post points out, the organizations that have optimized their supply-base will begin to open it up to new suppliers in an attempt to get even more value. Thus, if there was a super-cycle, it would be an oscillating contraction/expansion cycle that would emulate the cyclic cosmological model — an infinite contract/expand loop.

Diverging thoughts?

All Models Still Lead to Total Value Management

Not that long ago, Sourcing Innovation released “Taking the First Step on Your Next Level Supply Management Journey”, a white paper sponsored by BravoSolution that defined a simple 3-level maturity model that an organization can use to determine where it is on it’s Supply Management organizational journey. Noting that your organziation is either below average, above average, or best-in-class*, SI did not see any point in trying to be more complex (even though many industry associations, consulting firms, and analyst powerhouses will often proffer four and five level models).

And while the acronyms and acclamations — including VFS, Hi-Def Sourcing, Next Level Supply Management, Next Practices, and Value Chain Creation — will fly fast and furious, there is still one commonality among all leading models, including Gartners Global Trade Management Maturity Model, which is nicely summarized in this free white paper from Amber Road that offers “A Model for Value Chain Transformation”.

That commonality is something that the doctor has been prescribing for over five-years — Total Value Management (TVM). When you get right down to it, that’s what Strategic Business Enablement is all about. Maximizing value across the orgnization, end-to-end. In the sourcing process, the organizational model, the finance operation, the (information) technology platform(s), product management (& marketing), risk management, asset management, and relationships — the eight directions of the supply management navigator’s compass. QFD (quality function deployment), maximization of SUM (Spend Under Management), and end-to-end transportation management is all about extracting maximum total value for the organization. Demand creation, joint innovation, and new market entry is all about creating maximum total value for the organization.

And that’s why, if you’re not already there (above average and on the road to best-in-class), and more than half of you are not, you need to be moving to an advanced sourcing platform that supports in-depth spend-related analysis, decision optimization, collaboration, and market-informed category-based sourcing. These tools allow you to identify, maximize, extract, and retain value in your operations. For more information on these technologies, check out SI’s other recent white-paper, also sponsored by BravoSolution, on the “Top 10 Technologies for Supply Management Savings Today”.

*but not average as average can only be defined as an organization that is dab-smack in the middle of every other organization

There’s Sugar Indices. There’s Steel Indices. Where’s the Exuberance Index?

According to this very interesting article in The Sacramento Bee, the “Global Economy [is] in Worst Shape Since 2009”. Noting that six of the seventeen countries that use the Euro are in recession [including Spain, where protesters are pretending to be V], that the U.S. economy is struggling [yet again], and that the economic superstars of the developing world (namely, the BIC) are in no position to come to the rescue — since they are struggling too, the article claims that this crisis is knocking at all our doors.

But the reality is that crisis, while coming, will not occur until the world accepts it. Economies no longer follow GDP and growth, they follow market exuberance — the kind where housing prices double, where billions are made on junk bonds and collateralized debt obligations, and companies with zero sales get 100 Million valuations, and then go public with massive debt for no apparent logical reason. And it’s not the economic exuberance measured by CERES last year in their “Index of Economic Exuberance” where they tried to measure what’s been happening to whom since the financial crisis of 2008. (In this one-shot analysis, CERES developed a metric to measure whether a country’s macroeconomic performance is stronger or weaker relative to the prevailing performance prior to the advent of the global financial crisis in 2007 using output, unemployment, domestic demand, bank credit, inflation, and the real exchange rate.)

As long as markets are trending up, investment money flows freely. As long as investment money flows, people keep borrowing. As long as people keep borrowing, they keep spending. And as long as they keep spending, the economy goes up, even if production is falling, unemployment is high, and the cost of living is skyrocketing. And if the feds keep pumping money into the economy, the press keeps painting a rosy picture, and corporations take efforts to keep prices down, the economy can keep chugging along at an upward pace for months, and in the past, even a year or two, after everything should come crashing down. (The Zeroes proved that!)

Robert J. Shiller tried to capture the underpinnings of this phenomenon in his book, Irrational Exuberance, first published in 2000, and then revised in 2006, but even behavioural economics, in its current state, can’t capture the absurdity of what drives today’s market-driven economies.

But a technology may be near at hand. In the marketing domain, we have a new technology called sentiment analysis which uses NLP (natural language processing), CL (computational linguistics), and text analytics to identify and extract subjective information in source materials. Enabled by technologies such as the AlchemyAPI, which attempt to identify positive or negative sentiment within any block of text, the goal of sentiment analysis is to determine the attitude and tone of a document.

If we could apply such technology to all market analysis and market sentiments from investors, media, and influential self-publishers (journalists, analysts, and bloggers), it might be possible to see how the markets are moving and detect not only exuberance, but irrational exuberance. This is not as far fetched as it seems. As per an article in the MIT Technology Review in late 2010, the (gasp!) “Twitter Mood Predicts the Stock Market” (and since stock markets are among the primary drivers of economies, it’s a great start). According to the article, research conducted by Johan Bollen and colleagues determined, with an analysis of almost 10 Million Tweets from 2008 on, that stock market movements could be predicted with this data up to 6 days in advance! (Using a calmness index, they found an accuracy of 87.6% in predicting the daily up and down changes in the closing values of the Dow Jones Industrial Average. That’s a success ratio that will make your average trader blush!)

Twitter data alone would not be enough, but as we are better able to harness distributed computing power and the limits of Big Data approach the realms where even Chess becomes a solvable problem, analyzing all market related data for a day will become possible, and maybe we will be able to create an exuberance index and get a better grip on when a recession, even if overdue, will be upon us. (And then, as Supply Managers, determine the best times to sign contracts, lock in prices, and guarantee supply.)

Markets are Unpredictable – Is It Time For Old Fashioned Futures?

Recently, the Economist published a piece about the broken record that the markets have been following for the past five years. In particular, it has been skipping between two tracks – total chaos (as we experience one crisis after another) and a rhythmic predictability (as investors flee to the safest investment vehicles around, a sharp contrast to the early noughts when risk was everything and traders made millions on the press of a button).

According to the article, an ideal portfolio in 2007 would have been stuffed with gold, white sugar, Swiss francs and German bunds, anyone holding that mixture of assets when the crisis began would have seemed either eccentric or confused. However, over the past five years, a new kind of risk aversion has seen gold hit record values on almost 10% of trading days. So has the Swiss franc, white sugar, and government bonds.

At the same time, many other currencies and commodities have hit record lows as well as highs. Hedging, the standard trick of attempting to offset potential losses/gains that may be incurred by locking in a price too high (or low) for a desired commodity by also taking a position in another commodity that has traditionally followed a mathematically defined relation with the desired commodity, has become almost impossible as one crisis after another derails any and all attempts to find predictable trends.

However, before hedges, we had good old fashioned futures. Initially designed to allow a farmer to sell his crop for a fixed price before it was even planted, a future provided a farmer with an assurance that he would be able to sell his crop without losing the farm if markets went south. This not only benefited the farmer, but also benefited the buying company as they would be assured of a product at the time of harvest. Or, if they didn’t want it, the buying company could sell the contract to someone else.

In today’s volatile market, hedging is not the best idea. If you can’t lock a contract in at a fixed price, which should be your Supply Management organization’s number one goal, you should look to a futures exchange. While it won’t offer either party as much security as a good old fashioned contract, a futures contract may prevent either party from losing their shirt.

Any differing thoughts?

The Category Sourcing Scorecard – An Essential Tool for Collaborative Category Sourcing

Collaborative Category Sourcing is the foundation for eSourcing 3.0, whatever that happens to be. Why? As pointed out on SI, it is the only way to achieve savings above and beyond the limits of spend analysis and/or decision optimization, which max out at an average of 11% and 12% respectively, and this is especially true when the category has been strategically sourced (repeatedly). And the savings can be substantial. As pointed out in SI’s recent white-paper (sponsored by BravoSolution) on the “Top 10 Technologies for Supply Management Savings Today” (registration required), if the right combination of technologies are applied in the right way, they can often deliver 15%, 20%, 30%, and even 40% savings on hundred-million plus categories which were heavily scrutinized in the past and where little or no savings are expected. That’s why collaborative sourcing — which works best when it’s category focussed — is needed.

But how do you select the right category to start with? It’s certainly not as simple as selecting the category with the largest spend, the category with the least recent sourcing exercise, or the category coming up for renewal in six months. There are a number of internal, market, supplier, buyer, and category-specific factors that need to be taken into account — and this recent post on The Category Sourcing Scorecard over on CPO Rising did a great job of summarizing the vast majority of them.

Internally, the right category is the one with a contract maturing at the right time (which is typically three to nine months in the future, depending on the time it will take to do the sourcing project right), a documented sourcing history, a number of concerned stakeholders — who are willing to be engaged, and an accessible spend history (which, although not clear from the summary, should also contain usage, return, and inventory history).

From a market perspective, there should be enough competition to make an event worthwhile, the availability of one or more substitutes (if the current product has one or more patented, single-source, components), some bargaining power for the buyer, and barriers to market entry for both the product the buyer is producing and the capabilities offered by the suppliers (as, otherwise, new suppliers could set up shop overnight, sell to new buyers at cut-rates to establish business, and hurt your entire supply chain). In addition, the supply/demand (im)balance, which factors into the buyer’s bargaining power, should be known and relatively predictable.

From a supplier perspective, it should require some specialization (that the supplier can use to set itself apart), provide for profit margins, contain value-add components (valuable to the supplier and your customers), and a level of technical excellence. In addition, there should be suppliers who are financially stable, innovative, and willing to work with you to find substitute raw materials, components, designs, or production processes that will take costs down and push quality up.

From a buying perspective, there should be the potential to achieve some supply assurance, minimize production impact, save money, and require a production volume that will be attractive to the suppliers. In addition, there should be some signs that costs and risks can be reduced significantly enough to make the project worthwhile. This could take the form of falling raw material prices, the recent introduction of innovative new manufacturing technologies, or increased market competition.

From a category perspective, impact, complexity, and lead time will definitely be key factors, as noted by the post, but so could organizational importance, sustainability, and C-suite support. This will often be the hardest category to judge and score.

Which brings us to the following question – how do you score the scorecard? Do all the categories have equal weight, or are some more important than others? Making them all equal is certainly a valid starting point, as it will let you quickly eliminate categories that are really bad (with low scores in multiple categories), but may not be enough to let you choose between a category which scores great except for market factors, another which scores great except for supplier factors, and a third which scores great except for category factors.

In reality, the right scoring framework will be dependent upon the ultimate goal. If the ultimate goal is (still) to reduce cost, then the market factors should get the most weight. If supply assurance is the most important goal, then the buying factors should get the most weight. And if innovation is the desired outcome, the supplier factors should likely get the most weight. While it’s hard to make a hard and fast rul, here’s a good starting point for weighting.

 

To Focus On: Put a Higher Weight On:
Cost Market Factors
Supply Assurance / Risk Mitigation Buying Factors
Innovation / Value-Add Supplier Factors
Stakeholder Inclusion Internal Factors
Organizational Strategy Category-Specific Factors