True Savings Can Only Be Identified through Multi-Factor Optimization

A recent guest post from a vendor-employed guest contributor over on Spend Matters said to “Calculate Your True Savings Using Predictive Analytics”. While the doctor agrees predictive analytics can often give you a good data point as to projected savings, the reality is that it’s not always as accurate as you would like to believe and typically does not capture your best savings opportunities.

Why? Before we discuss the guest post, which did have some good points, we have to note that most predictive analytics algorithms work on trending and statistics on historical or market data, and while this can be highly accurate (95%+) the majority of the time (95%+), because market data is only historical and typically does not include data points on new (not yet introduced or announced innovations), detailed cost breakdowns on consumer / market prices, or operational insights into hidden inefficiencies whose correction can do more than shaving a few points off the top.

Going back to the post, the author states that if you use a Savings Regression Analysis (SRA) model based on multivariate regression of past-realized savings for a given subcategory to compute the savings potential under current market conditions, the target computed will be realistic, achievable, and likely mirror what you will do (despite the savings targets you set).

And this statistically based model will work if it is the same buyer (group) employing the same strategy on the same market base under similar conditions, but what could happen if a new buyer comes in that totally redefines the demand and the market strategy, or the market conditions have suddenly changed from supply shortage to supply surplus, or new production technologies could revolutionize production and trim overhead 20%? In this situation, this type of model will be significantly off.

Now, anything you can do to better predict savings is a positive, because, as the author points out, this allows for

  • better cash flow management (as you will better know your costs)
  • time to market optimization (as you will know the best time to source if you have leeway)
  • goal setting (as you won’t be trying to achieve the impossible)
  • performance management (as you can track against a realistic goal)

But while predictive analytics give a good data point, the best data point is when you use your market intelligence to build good should cost models, use optimization to minimize transportation and incidental storage and sales (and even taxation) costs (when sourcing globally), and use six sigma analysis to see if there is any opportunity to take cost out of a supplier’s overhead production cost. Going into this level of detail may indicate that while the product cost is likely to increase 1% this year (and explains why the predictive software says only 2% savings should be expected after heavy negotiations), an extensive analysis could show that a transportation network redesign could shave 3% and lean process improvements at your supplier could shave 2%, meaning that a cost reduction of up to 7% could be achieved with the right footwork (which is something the predictive model will never tell you). So use the predictive algorithms to establish a baseline, but never, ever stop there.

A Financial Health Check Should Be a Pre-Qualification of Every Supplier Qualification

And every organization should review a financial health or risk report, comprised of, or augmented with, third party data, and, unless they are (or have in-house) financial experts, this should preferably be done by a third party. The reality is that in today’s data driven world, no organization should be surprised by a bankruptcy of a mid-size or larger supplier that has been in business for at least three years. The probability of the vast majority of these bankruptcies are now predictable by financial analysts and while they may get a few wrong (as some companies may shape up just in time and others may fail faster than expected for a non-financial reason), they get a lot right.

And it’s not like financial ratings are hard to get anymore. While they are not as insightful, as they work exclusively on credit data and stock data compared to released financial statements (which is where the early warning indicators hide), most of the big data / credit services track enough data to come up with a reasonable financial risk score that at least lets you know whether, from a financial perspective, the supplier could be reasonably safe or is currently very risky — and needs a detailed analysis. Moreover, a financial health-focused offering by RapidRatings, and their FHR (Financial Health Rating) Report (which has been around for almost a decade), with an open example here, provides not only deep insight into potential risk, but the magnitude of the risk and the hard data for the risk — as well as the insights — and can detect risks from early warning signs that have not yet manifested in observable behavior (such as late payments).  In addition, RapidRatings’ new Financial Dialogue offering, which works in conjunction with the FHR, identifies the most important questions you should be asking your suppliers based on their health rating.  (An when you look at just the FHR report, you wonder why every organization is not doing at least this detailed level of supplier financial health analysis before committing a large or strategic spend to a supplier when all the data they need can be summarized in an easy to understand fashion.)

Now, you might say that because only one vendor, today, offers this depth of a report, which wasn’t previously available, and because the organization has done just fine without it for almost a decade, that you don’t need it, but SI would like to disagree. With global sourcing constituting so much of your supply chain, you don’t really know that much about your suppliers, their health, or the conditions in which they operate. And if they are supplying a custom made component, a raw material in limited supply, or a specialized service, the cost of recovery could be much greater than the initial cost of supply. These reports are becoming a necessity as part of your risk management.

SI is not saying you have to use RapidRatings or subscribe to their FHR reports (although they should be on your shortlist), but that you should at least do deep financial analysis on all of your strategic suppliers and use a platform to do it.  And while SI expects that other vendors with the same degree of analytic capability, financial know-how, and supplier insight — specifically Resilinc, FusionOps, and Simfoni — will soon attempt to release similar offerings, with their own unique spin, SI doubts that these other providers will be able to match the depth provided by RapidRatings for quite some time, as they are, respectively, focused on supply chain resilience, big data insights, and analytics on the go.  (However, if you are  currently using any of these vendors, you should work with them on their new analytic offerings as they can still offer other insights into the suitability of the supplier for your operation, assuming the supplier is financially viable enough to work with in the first place.)

While financial risk or financial health is only one KPI that should be used to analyze suppliers before qualifying them for inclusion in an event, it is an important one — the organization needs a supplier that will stay in business. Another KPI that should be included is a comprehensive CSR (Corporate Social Responsibility) assessment, as you want responsible and sustainable suppliers, and this can be obtained as well from vendors such as Sedex Global and Ecovadis. Finally, once the supplier has been deemed financially stable and sufficiently responsible, an overall supply chain risk rating should be computed (based on geography, risk of natural disaster, political interference, etc.). This will require either a risk management vendor (such as Resilinc, Risk Methods, etc.) or an analytics vendor that pulls in feeds from one of these vendors.

It’s a lot, but if you can be sure in your supplier, that’s one less worry in your overly complex supply chain.

BlueCart – Bringing Restaurants into the Modern Era!

BlueCart is an online ordering platform for small (and even mid-size) restaurant buyers in the food service industry, the distributors who serve them, and the sales representatives that manage the relationships. BlueCart is different than most offerings in that it is a hybrid freemium CRM/SRM platform designed not to help buyers identify the lowest cost, which doesn’t make much difference if you’re only ordering 10 units of something, but maximize their efficiency, allowing the buyers more time to focus on improving their business, growing their service capability, and, when appropriate negotiating their discounts with preferred distributors with a history of good, timely, service and quality. (In the restaurant industry, especially in the luxury restaurant industry, profits are highly revenue, and not cost savings, driven. The last thing you want to do is be unable to serve a potential customer, so assurity of supply trumps lowest cost, as it does in automotive where a production line halt can cost millions.)

BlueCart has made fairly fast penetration into the market, already signing up close to 8,000 restaurants and distributors, and should expand even faster when it closes its series B funding and ramps up its sales and marketing efforts and penetrates even more distributors. This is primarily due to fact that they are using a B2C freemium model where ordering is always free and secondarily due to the fact that distributors are incented to sell on BlueCart’s behalf since it makes order management and customer account management easier for the distributor than traditional phone-and-fax orders (especially if all of their customers are on the same platform).

The platform has two main components: the buyer platform and the supplier / distributor platform.

The buyer platform currently consists of basic order placement, messaging, supplier management, and simple reporting functionality as well as some new functionality around supplier and inventory management. The core functionality is the order functionality, which allows buyers to add to the cart using catalog search and custom-category drill-downs and per-level based ordering. Categories can be defined by food group (dairy, meat, seafood, etc.) or by inventory location which can make it incredibly easy for chefs and buyers to order what they need when they need it. Per-level ordering automatically computes order quantities based upon current inventory and pre-defined stock levels. Both methods add to a persistent cart that allows orders to be built up throughout the day so that both the buyer and the distributor can be sure the order is complete when it is submitted.

The supplier platform is centered around order, and catalog, management. When a supplier logs in they see their dashboard that allows them to jump into order management, catalog management, order fulfillment management, and analytics. The order management allows the supplier to see all orders, in all states, and filter by state, date, and customer. This allows a supplier to quickly zero in on the orders of relevance at any particular time. Embedded in the analytics / reporting module is the order fulfillment report that allows a distributor to, for each product (group), compile a list of all outstanding orders that need to be prepared (and put on the truck) for the day. This makes it very easy for the distributors to ensure that all orders in on time get accounted for and on the truck. Much easier than trying to compile the list from paper-based phone orders, e-mails, and faxes.

While the power of the platform is still pretty basic compared to mature e-Procurement platforms in the indirect sourcing space, it is (much) more powerful than what an average restaurant or small distributor, trying to manage orders and inventory off of ill-equipped spreadsheets, has ever had at their disposal. And, as such, deserves to be investigated. For more information, as well as a detailed SWOT assessment, watch for the upcoming Spend Matters Pro series (membership required) by the doctor and the prophet coming this week. It’s worth a detailed investigation!

One Hundred and Ten Years Ago …

The second remote control was demonstrated by Leonardo Torres y Quevedo (a Spanish engineer and mathematician) in the port of Bilbao in Spain, when he used his Telekino to guide a boat from the shore. The Telekino was a robot that executed commands transmitted by electromagnetic waves. (The first remote was Tesla’s patented “teleautomation”.) Even though this was the second example, it was the most important as it was built on Quevedo’s principles for wireless remote control operation that are still in use to this day.


What do you think LOLCat?

Don't Touch My Remote!

I Luv My Remote! I Evenz Sleep With It! Thank you Quevedo!

Eight Score and Four Years ago …

Air travel in the age of steam became a reality when the first dirigible, created by Henri Giffard made its maiden voyage from Paris to Trappes (in France). Filled with hydrogen, powered by a 3 HP steam engine, and weighing over 400 lb, the world’s first passenger-carrying airship was both practical (as long as you were careful about lighting that match) and steerable (as long as the winds weren’t too strong).