Monthly Archives: December 2014

Procurement Trend #10. e-Procurement Integrates Sustainability

We’re down to seven anti-trends. And even though most of the “future” trends we are now discussing are recent enough that the older generation can actually remember their beginnings with clarity, we need to follow LOLCat’s lead and find a way to stop the beat of the futurists‘ drum because, even with these trends that started in some of our life-times, the drum has been beaten to death and I still fear, like LOLCat, that the futurists’ may soon return to the age old art of cat-skinning to make a new one!

So why do these hare-brained futurists (who obviously re-enacted one too many Looney Tunes skits during wabbit-season) keep pushing the integration of sustainability into e-Procurement as a future-trend? Is it because, after years of real forward thinkers trying to convince the Businessman that cost-savings and sustainability weren’t diametrically opposed ideas, the futurists finally clued in? Or is it because

  • energy prices are going through the proverbial roof

    and they are grasping at straws trying to find a solution (and lucked on the right one)

  • raw material supply is running out

    and they finally realize the importance of sustainability in supply management, but since that’s not catchy, they chose to integrate it with the first concept they pulled out of their hat (and got lucky again)

  • CSR is increasing in importance with consumer concern

    and since customers are telling them to buy responsibly, and buying is e-Procurement, this must be the way to go.

Well, they are right. But leading companies have recognized this since the 1990s and have been doing this for well over a decade. They recognized that while renewable energy had a high-up front cost because it required large investments in solar panels, windmills, and turbines and new plants to either store excess energy produced during peak times in natural pump storage or huge battery arrays, it’s cost over time approaches pennies per Megawatt hours as sun, wind, and water power, unlike coal and oil, is free. Once the plant construction costs are paid off, it is just maintenance costs. It doesn’t matter if the technology is only 80% efficient and the pump storage only captures 60% of excess energy. The energy is free! Plus, these forward thinkers, unlike our futurists, also recognized that fresh water would soon be in short supply and invested in plant redesign to minimize water requirements.

Energy Prices

You need to go renewable to the extent possible and put plans in place to get to 100% renewable energy for all fixed operations and short-haul transport as soon as is feasible. While electric and bio-diesel may not yet be a suitable option for long-haul 18 wheelers, trains, and air-planes, electric and bio-diesel has bee proven cost effective for local courier delivery and hybrid has been proven cost-effective (by Walmart) for long-haul 18-wheeler transport. And if you build your own power plant, the long-term return from solar, wind, and/or water power, depending on where your operations are located, will be enormous. So there’s no excuse to not be using renewable energy for the majority of your energy needs. Plus, the first company to get 100% renewable for its operations gets huge bragging rights and brand karma!

Raw Material Supply

As per our post on increased raw material scarcity, you have to facilitate alternate designs that reduce or eliminate rare earth minerals and other expensive metals in limited supply and design for recycle in the interim so that you can recover as much as possible of the rare-earth minerals as possible to keep future costs down. (Preferably without outsourcing to a third-world country that breaks down your products in improper environments without proper containment and safety gear for handling your products that contain hazardous chemicals. No one wants your e-waste, especially if its hard to handle. If even India enacted anti-dumping legislations for e-waste, that should tell you something.)

Corporate Social Responsibility

We are approaching the point where it is no CSR, no sale, with many consumers, and as far as the doctor is concerned, it cannot come soon enough. We won’t knowingly put up with sweatshops and unsafe working conditions at home, so we shouldn’t put up with it in our supply chain. To turn a blind eye is hypocritical and, to be blunt, just unacceptable. It is time to get sustainability initiatives in place, embed ethics in the supply chain, and embed responsibility in the organizational culture. Suppliers don’t have to go the extra mile, but they should provide their workers with safe working conditions, a fair wage based on the local market, and actively insure that child labour is not used in their supply chain.

Procurement Trend # 11. Transparent Pricing

Only eight anti-trends remain. Doesn’t sound like much, but when you consider that we have been blasting away at these for two months now, it’s still a lot, especially since it’s going to take us another two and a half weeks to reach the last anti-trend that the futurists gave us. At least most of the “future” trends are recent enough that the older generation can actually remember their inception. (No, not the Leonardo DiCaprio movie!) But I have to agree with LOLCat that it would be nice if there was a way to stop the beat of the futurists‘ drum because, even with these trends that started in some of our life-times, the drum has been beaten to death and I fear, like LOLCat, that the futurists’ may soon return to the age old art of cat-skinning to make a new one!

So why do these hopped-up historians (who’ve obviously had one dozen lagers too many) keep pushing transparent pricing as a future trend? Besides alcohol-induced brain-cell asphyxiation, possibly because they’re still trying to figure out this new-fangled thing called a computer and still struggling to understand just what the world wide web can do for them. Regardless, it’s clear that they’ve just figured out that:

  1. the internet makes global commodity market data instantly accessible

    even in far-away places like China and Russia and Australia

  2. online marketplaces makes average market price data instantly accessible

    including prices that are actually paid by the public or contract prices that will actually be honoured because the contracts are with the public sector

  3. should cost models allow for reasonably accurate price estimation
    which can be calculated in real time using the data from #1 and #2

    so there is no excuse for not knowing when you are being over-quoted 20% by a supplier’s sales rep who thinks you are too dumb to know otherwise

So, what does this mean to you?

Commodity Markets

You should always know the current market price of any base commodity that you are buying and/or that the products you are buying are dependent on (if that commodity generally accounts for 10% or more of the product cost). You should subscribe to commodity market feeds, track them, and set up alerts anytime there is a significant change in prices one way or another over a short time period as this is often a signal to lock in a new contract (before prices climb to high), extend a current contract (if it looks like prices are going to skyrocket and then stay high for a while), or spot buy (if prices are declining and are expected to steadily drop over a period of time) until the time to lock in a new contract is right.

Consumer Marketplaces

You should always know the average price of any consumer good that you are buying in the open market or in the public market as public contracts are public! Don’t just rely on 3-bids and a buy for standard consumer goods, office suppliers, or other off-the-shelf purchases. Get baseline market data and negotiate from there based on leverage, economies of scale, and projected pricing trends.

Should Cost Models

Raw market data combined with local labour market data, local energy market data, and good should cost models will give you a good idea of what you should be paying for any custom manufactured good. Don’t go into a sourcing event without this baseline. If the suppliers have a history of colluding, and you don’t know it, that 5% you knock off of current pricing could still be 15% higher than what the supplier needs to charge to make a profit margin at the high-end of what suppliers in the vertical typically make.

So You Think You’ve Mastered Strategic Sourcing Decision Optimization?

Well, the doctor has news for you. You haven’t. In fact, you’re not even close.

You might be applying at least baseline optimization to the majority of your high-dollar and/or strategic categories. You might be in the Hackett Group Top 8%. You might be building Billion Dollar sourcing models. You might be years ahead of your peers. But the reality is that when it comes to true strategic sourcing decision optimization (SSDO) mastery, you’re not even close.

With the exception of the two e-CHAOS vendors, the doctor interacts and/or works with all of the remaining vendors who offer true strategic sourcing decision optimization (which isn’t a hard thing to do as there are only seven*1 [7] vendors in total with a solution that meets the minimum requirements as set forth in the wikipaper), knows the depth of the projects these vendors have supported, and can say with confidence that the best of the best have barely mastered the basics of optimization 2.0. Barely. And optimization 3.0 is on the way.

[  As a history lesson, optimization 1.0 was circa 2000 when the first solutions that minimally met the four basic requirements of solid mathematical foundations (MILP), true cost modelling, constraint analysis, and what if? capability hit the market. Most of these were basic, supporting only supplier – product – customer DC mappings; unit and transportation costs and then one level of discounts or rebates; capacity, allocation, and min/max supplier selection constraints for very basic risk mitigation; and manually created what-if scenarios. In addition, maximum model size was limited, large models took hours to days to solve, and setting up and importing all of the data from multiple bid sheets across multiple spreadsheets often took days.

Then, circa 2005 to 2007, as a result of a considerable increase in computing power, algorithmic improvements, and domain knowledge, a few solutions started to improve rapidly and we hit the beginnings of optimization 2.0. The platforms evolved to make full use of the theory of logical variables in the MILP solvers; they also supported multiple supplier locations, product substitutions, and differential costs by lane*2; a buyer could define costs by way of a cost model with as few or as many factors as desired, at multiple tiers and with volume or spend-based discounts; a full plethora of allocation, capacity, and risk mitigation constraints that could define required and desired splits, address risk mitigation or mandate awards to a set of products, suppliers, and or regions, etc.; and could automatically generate what-if scenarios based on automatically adding or dropping previously defined or newly defined constraints, historical versus current pricing models, and other factors. In addition, import and export was streamlined from RFX, Auction, spreadsheet templates, and ERP systems (where standard transportation and overhead pricing was kept). State of the art report generators and OLAP capability was integrated so that not only could you generate scenario reports and comparative reports across scenarios, but you could also dive in to see what was driving the savings against the current sourcing strategy and, more importantly, what was driving the costs compared to the unconstrained baseline scenario (and zero-in on what business rules might be too costly).  ]

The reality is that the average best-in-class organization is only doing T-CAP strategic sourcing decision optimization, and is still far from achieving TCO. Basically, when the average organizations build their cost models, they are focussed on the costs of acquisition and production (and distribution) of the goods they are buying. They’re not incorporating downstream maintenance, service and return costs and not considering end-of-life reclamation, recycling, and disposal. Nor are they breaking the acquisition cost models down to determine the upstream impact costs associated with the supplier or production method. For example, if the supplier runs their factory on dirty coal and the company has pledged carbon neutrality and has to buy carbon credits to achieve their goal or the working conditions in the factory are unhealthy (and the factory would be closed down if it was in America) and this adds more fuel to the fire of the CSR activists and is costing your organization brand value, these costs also need to be considered. As a result, the organization is capping its potential return from optimization. Not only is the organization not achieving TCO, but it’s no where close to achieving TVM (total value management), which is what it has to achieve if it wants to realize true optimization 2.0 mastery and move on to optimization 3.0.

And the average organization is not even thinking about the more advanced opportunities that the next generation 3.0 capabilities will enable. Right now, the leading strategic sourcing decision optimization vendors are integrating new capabilities in the new versions of their products that are currently in development, with some basic 3.0 capabilities already released! The convergence of big data, advanced analytics, and decision optimization into a single platform is enabling a host of new capabilities that the average organization has not yet envisioned, including the 6 next-generation advanced sourcing optimization capabilities outlined in Sourcing Innovation’s new white paper on Optimization, What Comes Next (registration required), sponsored by Trade Extensions (which is one of the vendors working hard to give you tomorrow’s optimization solution today).

Companies that master the 6 next-generation advanced sourcing optimization capabilities described in Optimization, What Comes Next (registration required), will not only be the first to master optimization 2.0, but will be the first to enter the world of optimization 3.0 and find savings and cost avoidance opportunities that they never even knew existed.

Are you ready to crank the amp and take it to 11? If so, download Optimization, What Comes Next (registration required) today!

*1 search the SI archives if you don’t know who the seven are

*2 the MindFlow Model, which was recognized as the first SSDO model to support multi-line item optimization back in 2000, actually supported this level of modelling back in 2000, an average of five-plus years before the majority of SSDO solution providers did