Monthly Archives: December 2013

Still Not Convinced You Need Your Invoices Under Control?

Then, for starters, maybe you need to dwell on the following:

  • You’re probably overpaying your suppliers by 1%
    because that’s what an audit recovery firm expects you are, and why they make a killing auditing the 20% of suppliers that constitute 80% of your purchase volume, because it’s not that hard for these specialist firms to identify overpayments of 0.5% that typically generate 500K or more in a gain share agreement for a few man months of work (or less)
  • There’s a 2 in 3 chance you are being defrauded of 2% of your revenue
    and that you’ll never notice because you aren’t able to verify all invoices
  • Up to 75% of your AP-related overhead is completely wasted
    on manual data entry, supplier inquiries, and other tactical work that adds no value to Finance or Procurement
  • At least 1 in 10 invoices have an error
    which could be as simple as missing payment information or as involved as incorrect pricing on every line item for a 200 line Bill of Materials because the supplier forgot to apply the discount
  • One Million invoices requires at least 100 standard 4-drawer filing cabinets
    if you get 1 M invoices a year, after 10 years, that’s 1,000 filing cabinets — where are you going to store them all??? (With today’s Storage Area Network densities, that’s 1 SAN. Which can be replicated in 3 places at almost zero cost compared to the seven figure cost of replicating and storing 10 Million invoices at three different locations.)

SI could go on, but the reality is that, especially if your organization is growing, it really, really needs to get its invoices under control. To find out how it can do this, download SI’s new white paper on An End-to-End Invoice Automation Framework Benefits & Best Practices, sponsored by Nipendo. (Registration required.) Once you understand the requirements for a true end-to-end invoice automation solution, you will be well on your way.

Is the Emerging Share Economy Going to Disrupt Your Procurement Practices?

My Purchasing Center recently ran a very interesting article from a Senior Consultant of the Hackett Group on “Considerations for Supply Chain and Procurement in the Share Economy” that did a great job of explaining how the Share Economy is disrupting consumer purchasing patterns, and thus demand. However, in SI’s view, it did not do as great a job when it came time to make the case that it would disrupt daily Procurement operations.

In SI’s view, while the share economy may change the approach to certain categories, it’s not going to change fundamental procurement processes, methodologies, or the best practices that a leading Procurement organization brings to the table. We will elaborate on this, but first let’s review the main points of the My Purchasing Center article.

Noting that the share economy is projected to reach 3.5 Billion this year, with no signs of slowing down, the author of the My Purchasing Center article posits that these trends are going to have a significant, innovative, and potentially disruptive impact on Supply Chain and Procurement.

Zeroing on on services like Lyft and Airbnb where legions of people use their own car or living space as an on-demand taxi-service or rental, the author notes that this reduces the demand for additional cars and short-term rental properties. Similarly, services like zip-car, where people can rent on demand, not only reduce the demand for taxis and limos, but for second vehicles altogether, and thus reduce the total demand for vehicles from a manufacturer. This can effect economies of scale, and increase the cost of each vehicle produced if the demand drop is significant.

Then there is the emergence of 3D printing that is now to the point where even non-engineers can assemble a 3D printer, download some software, and produce their own goods at home. When the cost drops, demand for products that can be just as cheaply printed at home may drop but, more importantly, demand for products that can be printed in bulk just as cheaply as needed on the shop floor could wipe out entire categories for a supplier.

And these are valid observations. Demand is going to change, and shift, and it’s going to have an effect on what an organization can and can’t sell and on what a supplier can and can not profitably produce. No argument there.

But, unless it takes us back to a barter economy, it’s not going to have much of an impact on a good Procurement organization. The first thing a good Procurement organization does when it starts a sourcing event for a category is analyze the category in depth to determine the demand for the product or service, the criticality of the product or service, the strategic nature of supply relationships in the delivery of the product or service, etc. to determine what supply strategy is the most relevant, how the sourcing event should be conducted, what technology should be brought to bear, etc. If demand has dropped 50% in a category since it was last sourced and the economies of scale have diminished, then sourcing is going to shift from a lowest TCO approach to a strategic relationship where it can work with the supplier to take cost out of the production or delivery process or, if necessary, innovative a new design that will allow it to use lower cost materials and production / delivery processes. With or without a share economy, the mandate, and function, of Procurement is the same — source each category in the manner which generates the most value to the organization and procure each part or service against the identified strategy.

Do you think SI is missing something? If so, leave a comment.

The Value of Visibility: It’s More Than You Think

When someone mentions supply chain visibility, the first thought that probably jumps into your head is a foundation for resiliency, which it is, as we discussed in our last post on the value of visibility in your supply chain. The potential to prevent a major supply chain disruption that could cost an organization an average of 10% against potential revenue on the affected product lines for two years running and reduce that loss to 2%, or less, is huge. But it’s not the only savings enabled by good supply chain visibility.

In addition to per-event savings associated with disruption avoidance and crisis containment, there are ongoing savings associated with spend under management. Even if your organization employs advanced sourcing methodologies that include spend analysis and decision optimization, the value of multi-tier visibility goes well beyond what traditional advanced sourcing models can deliver.

For example, a 2012 FERMA4 study found that the majority of firms with advanced risk management practices, built on good end-to-end supply chain visibility, had EBITDA growth over 10% and revenue growth over 10%. The EBITDA growth came from lower costs. The lower costs resulted from better sourcing decisions enabled by better multi-tier supply chain visibility and total cost-of-ownership models. That’s a double digit savings! Up until this point, only spend analysis and decision optimization could consistently deliver that level of savings.

The observant among you might be thinking that this study is just one data point and maybe these savings aren’t obtainable by everyone because it’s statistical, but the proof doesn’t end there. In 2011, Haitao Li and Mehdi Amini undertook a comprehensive computational study on a five-tier multi-echelon supply chain for PC assembly that analyzed over 2,000 scenario variations and found that multi-tier visibility drives cost savings of 15% on average. This study, which built in the impacts of potential, and likely, supply chain disruptions at various levels of the supply chain, demonstrated that most optimal awards that only consider the first tier are highly dependent on the input assumptions and extremely susceptible to disruptions, which can increase the cost by up to 60%! Even the tiniest of perturbations was found to increase the total cost by over 5%. But when multiple tiers were considered and awards were made that were disruption resistant, the average cost savings came out to 15%! This is huge! (Especially given that, according to research conducted by IBM referenced in our last post, emergency re-sourcing efforts often increase costs by up to 30% over the optimum solution.)

This means that, even if your organization is lucky enough to be among the 14% that don’t experience a major disruption within the next year, the ROI from better sourcing decisions alone will pay for a supply chain visibility solution many times over. How much will you save? Up to 1.7% of revenue every year. (An average manufacturer will spend 59% of revenue on direct materials and services and 89% of this spend under management. Assuming that at least 1/3rd is sourced annually, and that the savings are only 10%, as per the FERMA4 study, that’s savings opportunity of 0.10 * 0.33 * 0.89 * 0.59 = 0.017 = 1.7%) So, if your organization does 1 B in revenue, it can expect a savings opportunity of up to 17 M a year from disruption-resistant awards to the supply base (which will, by their very nature, minimize the number of small disruptions the organization experiences).

And this is only one aspect of the year-over-year recurring savings that Supply Chain Visibility can bring your organization! For a deeper insight into the other ways in which Supply Chain Visibility can bring your organization recurring year-over-year savings, download SI’s latest white-paper on The ROI of Supply Chain Resiliency: It’s More Than You Think (Registration Required), sponsored by Resilinc. You might be surprised at just how much hidden value you can extract from your Supply Management operations with good visibility and resiliency.

Basware: P2P for the Global “E”

Basware is one of the largest players in the global procurement arena. Founded in 1985 in Espoo, Finland (as Baltic Accounting Systems) to deliver enterprise finance software solutions, the company (which is now public and traded on the NASDAQ OMX Helsinki Ltd. as BAS1V) has grown from a small country player to a global platform with over 2,000 international P2P customers that collectively do business with almost 1 Million companies in over 100 countries. Basware supports its global customer base through its operational footprint that spans over 50 countries on 6 continents and includes over 100 partners and resellers.

It’s solutions span the entire P2P (purchase to pay) process, from requisition through payment and post-transaction analysis and includes the Basware Commerce Network that enables over 425 Billion of e-commerce annually. The network currently lists 1.9 Million suppliers and processes over 60 million e-invoices annually through the 60+ e-invoice formats it currently supports, including XML, EDI, and Virtual Printer formats. The network is growing and transaction growth is currently running at 60% year-over-year, and now that they have partnered with MasterCard to provide their customers access to MasterCard’s suite of payment products, it is likely that network growth will accelerate even more now that customers have even more payment options.

One of the most unique features of the platform is the fact that it spans the full AP and P2P cycles, whereas many of the smaller P2P and e-Procurement platforms are Procurement centric, with little support for AP. However, Basware started as a provider of finance solutions and migrated to the e-Procurement space with the birth of e-Commerce, and, as a result, has a firm command of the order-to-cash cycle from both organizational viewpoints.

From the procurement side, the platform contains modules for analytics, basic sourcing (RFX), contract management, catalog management, e-Procurement, and e-Invoicing. From the AP side, the platform contains modules for e-Invoice Processing, e-Invoice Matching, e-Payment, and Analytics. All modules are integrated with a consistent look-and-feel, and all modules are available on top of Basware’s new cloud-based Alusta platform which supports (multi-)enterprise private cloud instances. In addition, the collaboration capabilities and social integrations span the entire platform and all data in the platform is available to the analytics module.

Another unique feature is that Basware has decided that they are a procurement platform, and not a sourcing platform, and that their sourcing capability will remain basic. Basware recognizes that Procurement experts are not Sourcing experts and vice-versa, and have decided that they are going to partner to delivery an industry leading sourcing solution for those customers that need end-to-end Source-to-Pay functionality. As a result, they recently announced a major partnership with BravoSolution to deliver a comprehensive source-to-pay solution that covers all key steps of the sourcing, procurement, and finance process.

In future posts, SI will dive into key capabilities of the Basware Commerce Network; the e-Invoice processing, matching, and payment capabilities; and the analytics platform.

SI Still Prefers Big Brains to Big Data, But If In Big Data You Trust …

… then trust fully and completely as the one thing that Big Data can do (besides sucking up a lot of your cash for a dubious ROI), when properly mined, is overcome the Three Cognitive Traps that Stifle Global Innovation.

How? We’ll get to that, but first let’s explain what the three cognitive traps are.

The Experience Bias

Referred to as the availability trap by the authors of the HBR post, it refers to the fact that many people assume an element of a culture that they, and their peers, are familiar with is representative of that culture. The example given by the authors is that Brits see Chicken Tikka Masala as representative of typical indian cuisine as that is what is common in the British curry houses. Similarly, most North Americans think that fried rice and egg rolls are representative of typical Chinese cuisine, as that is what comes with just about every combination plate in every Chinese restaurant. In both cases, this is not true.

Similarly, in the business world, most executives in the developed world believe that the urban, affluent, rapidly growing middle class is representative of the population of a market in a developing country they are going after. The urban middle class is only a small percentage of the population in many developing countries, and not representative of the market as a whole.

The Confirmation Bias

The confirmation bias is when we use ambiguous data as clinching evidence of our hypothesis. The example given by the authors was how a European multinational, despite being told by their Indian salesforce that their building material product line was over-engineered for much of the Indian market, refused to listen (believing that the local salespeople just did not have the required skills to sell the product) and sustained years of losses, including two country CEOs, before it saw the error of its ways. Why did this happen? Early on, a global product executive visited India and happened to be present when a single, stellar, salesperson encountered a high-value customer, patiently demonstrated each and every superior product feature, and, after a significant amount of time, finally made the sale. This one data point of success was focussed on despite the fact that there were countless data points of failure.

The Variance Bias

The variance bias (known to psychologists as out-group homogeneity bias) is where we (drastically) underestimate variance in distant cultures, grouping all Chinese consumers into one market segment, for example, while separating New Yorkers and San Franciscans into two completely different market segments (due to our familiarity with both market groups and in-depth knowledge about their differences relative to our understanding of the Chinese marketplace). (There are 1.35 Billion people in China. Do you really think they are all the same? There should be considerably more market segments in China than in the US.)

With enough data, and the willingness to blindly trust the data, Big Data will overcome all three of these biases. Since big data relies on transactions and facts, and not the limited pool of experience associated with a decision maker, the real patterns (and not the perceived one) will quickly emerge. Similarly, outliers (such as the example of the stellar salesperson who got lucky) will quickly be eliminated and bad hypotheses will not be confirmed. Finally, a good algorithm won’t group data that doesn’t belong together and if it takes 25 clusters to properly segregate the data, the algorithm will return 25 distinct clusters for human analysis and interpretation.

However, as you probably guessed, SI doesn’t believe that you need Big Data to overcome these traps. Big Brains will suffice. As the authors note, a curious open mind who does her research can overcome each of these traps. An open mind who realizes she doesn’t know much about a market and dives into it, reviewing local research and local media, will get a more realistic perspective than one which makes snap decisions based upon his limited experience. An analytical mind that looks at the ratio of success to failures in sales efforts will quickly see that the close rate is way too low, something is wrong, and a thorough investigation is needed. And an inquisitive mind that asks if the market has been thoroughly covered will realize that studies and data that only cover urban centres don’t cover the population as a whole and additional research into non-urban lifestyles, tastes, and buying patterns is needed if the company wishes to reach that market.

Big Data is needed if you want a reasonable chance of accurately predicting the weather beyond the next 24 hours, modelling stresses on a spacecraft under different adverse conditions, or brute-force breaking the SHA-256 algorithm. It’s typically not needed to get a good handle on a potential market and good product design. Brains effectively put to use will do just fine in these situations, as they have for hundreds of years.