Category Archives: Spend Analysis

Scared of AI? Try Auto-Classify!

Last week we noted that if you were scared of AI (and rightfully so, as it tends to over-promise and under-deliver), you should start with Auto-Buy — specifically, auto-buy for certain tail-spend products and services where the platform can at least get you market average pricing on a product or service you’re likely overpaying by 15% or more on. The platform might not be able to match the best expert, but it can far surpass an average buyer, and paying market average is better than overpaying by 15%.

In this post we said that your spend generally breaks down into strategically sourced, bought from the GPO, catalog buy, and the rest falls into the tail. And the way to save significant money quickly and easy is to get the tail out of control … a large tail spend can be costing you 6% against the bottom line. That’s huge. And there’s only one way to get this under control. Auto-buy. And there’s only one way to do better — get the spend out of the tail into the other categories.

This is easier said then done. Tail spend might only be 20% of the spend by dollar, but it’s 80% to 95%+ of spend by volume — trying to classify each and every purchase to a strategically source, GPO, or catalog category it could fall into is a monumental task, and that’s why the tail spend stays high,

But it’s not a monumental task for AI. Remember, we can’t do millions of calculations a second – computers can. And when enough of these calculations are done, and correlated, computers can make assignments that, on average, greatly exceed the accuracy of an average buyer in significantly less time. Plus, the rare-misclassification will be found quickly by a human buyer and re-assigned to the right category — either the product has an equivalent in the GPO, or it doesn’t. Either it has an equivalent in the catalog, or it doesn’t. Or it fits the way the strategic buyers buy, or not. But in the first two cases in particular, the computer will be not only be able to identify the best matches with high accuracy, but even provide its reasoning.

So use the AI for what it’s good at — bulk computation and analysis. And be confident that while it will greatly reduce your tactical workload and make you more efficient, it won’t replace you — in fact, it will make you irreplaceable as you will be freed up to spend more time on the strategic, value generating work.

Category Management Savings Drying Up? Time to Cross-Optimize!

Leaders know that the best way to savings success, especially when the CFO and CEO demand savings today (even though this could sacrifice value tomorrow), is category management — a razor sharp focus on buying like products from like suppliers that allows for apples-to-apples comparison across products on key dimensions of price, quality, warranty, lead-time, etc. so that the best buy that meets the mandatory savings target can be made every time (and as much value preserved in the category as possible).

But Leaders also know, just like the third auction in a row increases costs, good category management sees savings fall rapidly as the fat is quickly squeezed out of the margin and the waste quickly squeezed out of the production, delivery, and inventory process as everything is optimized. This means that as soon as raw material costs go up, category costs go up, and not down.

This can be problematic when (unrealistic) expectations are placed on the Procurement department year after year and savings need to be found even when, apparently, none exist. But here’s the thing, while they don’t exist in the raw materials, or even the overhead, of production, they do exist in the distribution and inventory and still exist in the volume. But only in volume beyond what’s in the category.

This means that the only way to extract them is to increase the volume, which means that you need to simultaneously cross-source and cross-optimize across categories that can be shipped together from the same supply base. For example, while it might be logical to separate brass, bronze, and copper parts from a category management perspective, considering that some suppliers will likely supply parts across these categories (considering brass and bronze are alloys that contain copper), from a sourcing perspective it makes sense to source all three categories simultaneously. This way you can optimize logistics and negotiate additional volume discounts based on spend levels.

This also works in CPG — a supplier may supply computer devices, audio devices, and home security devices — and while you may want to manage these separately, you want to source them simultaneously. And it will work across seemingly unrelated categories if you are buying from suppliers that are essentially distributors (like office supplies vendors, MRO vendors, etc.). All you need to do is find a set of categories where the majority of products come from the same supply base. How do you do this? Simple: use a modern spend analysis tool.

And how do you source multiple categories simultaneously and cross-optimize logistics, inventory, and discounts for the lowest overall total cost of ownership (while maintaining value)? Strategic sourcing decision optimization — the technology SI has been telling you to acquire for a decade. Which vendor? Whichever one suits your needs best. Coupa, Jaggaer ASO, Jaggaer Bravo, and Keelvar are all great. Determine is re-building the Iasta capability on the b-pack platform, and when complete, will join the A-list again … and BidMode is about to hit the scene. Just get one, so you’re not left behind.

Why Bother Classifying Spend? 3 Ways Spend Analysis Will Improve Your Life … Part II

Today’s guest post is from Brian Seipel, Spend Analysis lead at Source One Management Services focused on helping corporations gain a clear view of their spend data to derive actionable budget optimization strategies.

Yesterday we began our tale of two VARs that have a lot in common. Both serve the same North East region, both offer stellar customer service, and so far the relationship has been good on all sides. Each of your offices comes away satisfied after reviewing their VAR’s track record. But, as we started to discuss yesterday, that’s not all there is to the story. Today we discuss the next two ways spend analytics can change your life … for the better.

Improve Efficiencies

Beyond hard dollar savings, companies stand to save money by building a leaner, more efficient Procurement department. From the benefit described above, we can already see how our total vendor pool will be reduced through consolidation, and fewer vendors to manage means less time devoted to the procurement process. However, we will also learn more about our vendor landscape through the analysis.

Continuing the example above, let’s consider those two VARs a bit more closely. All else equal, we may find out that New York’s VAR offers a vendor-managed inventory program, centralized billing, and an online customer ordering portal. Each of these value-adds will help Procurement be more efficient, even if no hard dollar savings are generated. By properly researching the landscape, we can determine what value-adds are truly important and focus on building up these efficiencies.

Clamp Down on Maverick Spend

So far, we’ve consolidated spend to a single VAR (generating hard dollar savings via negotiated rebates and unit pricing using our newly consolidated spend as leverage) and improved our procurement process (generating soft dollar savings by understanding and implementing best practices).

We haven’t, however, talked about specific items being purchased. As the saying goes, “the devil is in the details,” and the very best supplier relationships can fall prey to maverick spend if employees are left to their own devices.

Consider all of the non-strategic, commodity spend that will pass through our VARs; items like cabling, computer peripherals, office equipment and a whole host of other small purchases are often included in contract pricing lists. But what about an employee who goes off the reservation, and orders off-contract? Your negotiated rates become meaningless. Would the purchase of an off-contract mouse by a single employee that is $5 more expensive break the bank? Likely not – however, this problem can get out of hand quickly if large groups of employees routinely ignore the on-contract equivalents. Analyzing spend and comparing it to negotiated on-contract items allows us to identify the problem and either reign in employee behavior, renegotiate the contract price list, or a combination of both to solve it before it gets out of hand.

Which Camp are you in?

If there’s one thing our tale of two VARs has taught us, it is that “you don’t know what you don’t know.” Neither VAR may look like a poor partner at the outset. However, when you look at the entire picture, room for improvement becomes more obvious (especially if we’re willing to change it up). We simply can’t see that entire picture without performing a spend analysis in the first place.

By performing our spend analysis, we put ourselves in the position of moving between the three-foot and 30,000-foot view quickly, enabling us to look at our spend and supplier relationships from all sides. Only then can we effectively manage our spend.

Thanks, Brian.

Why Bother Classifying Spend? 3 Ways Spend Analysis Will Improve Your Life … Part I

Today’s guest post is from Brian Seipel, Spend Analysis lead at Source One Management Services focused on helping corporations gain a clear view of their spend data to derive actionable budget optimization strategies.

Let’s face it, you and your team have your collective hands full keeping the Procurement trains running each day. Adding a spend analysis initiative on top of everything else being juggled? Well, that may be one ball too many to keep in the air. It seems like an unnecessary added step you simply don’t have time for and, really, what’s the point?

Through years of working with clients to develop and execute strategic sourcing initiatives, I have found there are two camps I can sort organizations into. Which side a client lands on is indicative of how much work lies ahead in terms of helping them truly control spend. Organizations will either be pro spend analysis… or barely spend time on the subject, if any at all.

To be fair, many organizations run a tight ship in terms of managing spend – but there’s still room for improvement for a good number of others. There are some great reasons to make a proper spend analysis a priority. As such, I wanted to take a minute to extol the virtues of this process to show some of the benefits you may be missing out on. See below for my top three reasons a proper spend analysis should be the next initiative you spend some time on.

A Tale of Two VARs

(Value Added Resellers)

First, I’d like to set the stage a bit. Consider the relationship between an organization and its IT hardware/software value-added resellers. In this scenario, we have two such VARs; one servicing the organization’s New York branch, the other servicing Philadelphia.

These two VARs have a lot in common. Both serve the same North East region, both offer stellar customer service, and so far the relationship has been good on all sides. Each office comes away satisfied after reviewing their VAR’s track record. But is that all there is to the story?

Generate More Savings

One of the most apparent (if not THE most apparent) reasons to analyze your spend is the impact such an analysis has on strategic sourcing initiatives. At the most basic level, an organization needs to know several key facts before developing a strategy around cost savings:

  • “How much money are we spending, and who is spending it?”
  • “Who is that money going to?”
  • “When are these transactions happening?”

These seem like simple enough questions, but getting the answers can be tricky. To kick off our VAR example, one great way to save money with such VARs is to leverage your spend volume to negotiate rebate structures and develop reduced unit pricing for all purchases. The more you spend, the bigger the rebate and the greater the incentive for VARs to offer unit price discounts – and these things can add up quickly. Consolidating spend to as few VARs as possible helps to maximize this strategy, and both our VARs service the same region. However, because New York and Philadelphia each use two separate VARs, neither will be able to negotiate as strong a rebate, and we likely won’t make much progress in commanding discounted rates. Each location may have a great relationship with its respective VAR – and Procurement wouldn’t know they were missing out on a savings opportunity until a spend analysis revealed this missing piece.

But this is just one way spend analytics will change your life.

Thanks, Brian.

Introducing LevaData. Possibly the first Cognitive Sourcing Solution for Direct Procurement.

Who is LevaData? LevaData is a new player in the new optimization-backed direct material prescriptive analytics space, and, to be honest, probably the only player in the optimization-backed direct material prescriptive analytics space. While Jaggaer has ASO and Pool4Tool, it’s direct material sourcing is optimization backed and while it has VMI, it does not have advanced prescriptive analytics for selecting vendors who will ultimately manage that inventory.

LevaData was formed back in 2014 to close the gaps that the founders saw in each of the other sourcing and supply management platforms that they have been a part of over the last two decades. They saw the need for a platform that provided visibility, analytics, insight, direction, optimization, and assistant — and that is what they sent out to do.

So what is the LevaData platform? It is sourcing platform for direct materials that integrates RFX, analytics, optimization, (should) cost modelling, and prescriptive advice into a cohesive whole that helps a buyer buy better when they use and which, to date, has reduced costs (considerably) for every single client.

For example, the first year realized savings for a 5B server and network company who deployed the LevaData platform was 24M; for a 2.4B consumer electronics company, it was 18M; and for a 0.6B network customer, it was 8M. To date, they’ve delivered over 100M of savings across 50B of spend to their customer base, and they are just getting started. This is due to the combination of efficiency, responsiveness, and savings their platform generates. Specifically, about 60% of the value is direct material cost reduction and incremental savings, 30% is responsiveness and being able to take advantage of market conditions in real time, and 10% is improved operational efficiency.

The platform was built by supply chain pros for supply chain buyers. It comes with a suite of f analytics reports, but unlike the majority of analytics platforms, the reports are fine tuned to bill of materials, component, and commodity intelligence. The reports can provide deep insight to not only costs by product, but costs by component and/or raw material and roll up and down bill of materials and raw materials to create insights that go beyond simple product or supplier reports. Moreover, on top of these reports, the platform can create costs forecasts and amortization schedules, track rebates owed, and calculate KPIs.

In order to provide the buyer with market intelligence, the application imports data from multiple market fees, creates benchmarks, compares those benchmarks to internal market data, automatically creates competitive reports, and calculates the foundation costs for should cost models.

And it makes all the relevant data available within the RFX. When a user selects an RFX, it can identify suppliers, identify current market costs, use forecasts and anonymized community intelligence to calculate target costs, and then use optimization to determine what the award split would be, subject to business constraints, and identify the suppliers to negotiate with, the volumes to offer, and the target costs to strive for.

It’s a first of its kind application, and while some components are still basic (as there is no lane or logistics support in the optimization model), missing (as there is no ad-hoc report builder, or incomplete (such as collaboration support between stakeholders or a strong supplier portal for collaboration), it appears to meet the minimal requirements we laid out yesterday and could just be the first real cognitive sourcing application on the market in the direct material space.