Category Archives: Spend Analysis

Contract Compliance Trust But Verify Part I: Compliance Data


Today’s post is from Eric Strovink, the spend slayer of spendata. real savings. real simple. Eric was previously CEO of BIQ; before that, he led the implementation of Zeborg’s ExpenseMap, which was acquired by Emptoris and became its spend analysis solution.

If you have a contract with a vendor, that’s good news — you’re not paying list prices any more. At least, that’s what should be happening.

It’s fascinating what can really happen. We’ve recently seen a vendor raise prices in a distant region while maintaining contract prices in the headquarters region. This and similar disparities aren’t necessarily deliberate — mistakes can be made by anyone. Even items purchased through an e-procurement system can fall off the price-compliance applecart as a result of exception-handling processes. The lesson is that “Trust but Verify” is a necessity, not a nicety. And, since manual inspection of a large volume of items and invoices is impossible, this process must be mechanized.

The good news is that many goods and services can be standardized with a fixed price. These items can easily constitute 25-30% of spending. For these goods and services, contract compliance is (at least conceptually) straightforward. Examples include physical items, such as computers, office supplies, phones, furniture, MRO parts, facilities supplies, vending items, security equipment, mobile phone plans, stationery and forms, promotional items — even some types of software. Services examples can include cleaning, appraisals, training classes, recruiting, records management, armored car, overnight mail, hotel, and car rentals (when they are for a fixed unit of time or work).

If contract compliance for these goods and services is straightforward, why doesn’t everyone do it? As usual, the devil is in the details.

  1. Who builds the (usually spreadsheet) compliance model?
  2. Does the model show who is buying off-contract items from the vendor? Which items? When?
  3. Who loads next month’s data into the model, and adapts it accordingly? What’s the cost of this, versus the payback?

For these questions, invoice data, aka Price X Quantity (PxQ) data, is required.¹

Acquiring Data

PxQ data is best acquired directly from the vendor. It’s your data; you have a right to it; and you’ve a right to ask for it. Many vendors will supply it in a reasonable format, such as in an Excel spreadsheet, or as a CSV or DSV file. Some vendors, though, will attempt to discourage you by providing data in an unreasonable format — for example, by supplying every invoice they’ve sent, in PDF format, as an individual file (don’t laugh; we’ve seen this). You may want to consider whether doing business with that vendor is in your best interest moving forward. Certainly you should write into any future contract that the vendor must provide PxQ data in a reasonable format.

But, you also need contract data — that is, contract price by item. That data is probably already in a reasonable format, for example as an addendum to the contract. At worst, it can be keyed in manually or minimally edited into shape.

So, there are two datasets to consider. The first, consisting of invoice level PxQ data, comes from the vendor and resembles this:

Click to enlarge

The contract pricing, which you should already have, resembles this:

Click to enlarge

Once you have the data in this form, you can easily figure out whether the contract is leaky or solid. We’ll continue this discussion in Part II, Monitoring the vendor.

Thanks, Eric!

¹Accounts Payable-based spend analysis can help to determine what spend is definitely not under contract. But it is helpless to address contract compliance issues.

Do You Need Spend Analysis?

DOES YOUR ORGANIZATION SPEND MONEY?

No. You don’t need spend analysis.

YES! YOU NEED SPEND ANALYSIS!

And don’t say you can’t afford it. Given that Spendata offers a single user annual license to a best-in-class do-it-yourself tool for $699, you can afford it. And when you consider companies like Spendency offer enterprise do-it-yourself solutions starting at the 3K/month price point BIQ used to start at (and SpendHQ isn’t that much more per month with their entry level offering) and once you set up the mappings, you’re set to go, you can. Especially when you can use it to identify an average savings of 10% year over year.

And don’t tell me that do-it-(mostly)-yourself is not an option. It always is! You just need a bit of training. And that can be obtained at an affordable price point as well. Contact Data-TrainingWorx limited about their SpendataWorx program, which can include an LMS consisting of 40 online interactive videos and over 800 two page “microbite” documents that is everything you need to know to get started and analyze your data … for years!

Remember, you need it, you can afford it, so just get it, and just do it.

Are You Ready to Get Analytical But Don’t Know How? Read On!

Now that you’ve read our last three posts and understand that you need to get more analytical if you want to get cognitive, hopefully you’re ready to dive deeper but just don’t know how to do that.

The four part answer is almost as easy as it was for optimization, just a bit more nuanced. What’s the nuance? Figuring out if your provider offers a modern spend analytics platform or is still a generation (or two) behind (when you are still behind yourself) is the nuance. So how do you determine if a vendor at least passes the sniff test? We’ll get to that, but first, let’s talk about where you start.

At a high-level, the four-part answer is almost the same as optimization. Just the vendor names change.

1) If you are using a sourcing or analytics platform from a modern provider with modern (next generation) analytics capability, use it (and acquire the module if necessary).

Who are the vendors? While we can’t say this list is thoroughly exhaustive, if you look at Spend Matters Deep Solution map, you see that the following providers make the map: AnyData, (SAP) Ariba, (Opera) BIQ, GEP, iValua, Jaggaer, Sievo, Simfoni, SpendHQ, Synertrade, and Zycus. Not all are equal, and this list is likely not exhaustive, but depending on your organizational needs, a sub-set of these providers is likely your starting point. (What Sub-Set? Depending on whether you are data, function, process, technology, configurability, or services oriented, the sub-set will vary. And practitioners who want to know which vendors match which subset can contact Spend Matters.) And if you are a do-it-yourself type, you could probably start with a platform like Spendata.

2) If you are not using a modern analytics platform or a modern sourcing platform with analytics, get a modern analytics platform or a modern sourcing platform with analytics, your choice.

Again, you can start with the dozen of providers above, which you can quickly narrow down depending on whether you prefer best of breed or sourcing suite and whether you favour technical orientations or service orientations. If the list is still too large, find the subset that bests fits your organizational size, industry, category focus, geography, and culture and focus in on those.

3) If you are using another sourcing or analytics (reporting) platform that is not meeting your needs, and can replace it, do so.

As with the optimization providers, a few of these providers have a considerable portion of their customer base that consist of customers that switched from another provider with a solution that didn’t meet their needs and, thus, have a lot of experience with change management, fear squashing, migrating your data over, and getting you up and running on the right processes quickly. Simply craft the right RFI and you will quickly zero in to the handful of providers that will likely be the best fit for your situation.

4) If you are using another sourcing platform or reporting platform that is otherwise meeting your needs, or can’t be replaced at the present time, or both, augment it with a pure-play deep-dive best of breed modern analytics solution.

So if you are in the situation that you just bought a best of breed Source-to-Contract or Source-to-Pay solution and can’t replace it, or you have a first generation BI tool that produces reports the executives love but doesn’t meet your needs, augment it with a point-based best of breed solution. From the above list,
AnyData, (Opera) BIQ, Sievo, Simfoni, SpendHQ, and Spendata fit that bill.

But what about the “sniff test”?

How do you differentiate a last generation solution from a current generation solution? Three tests. Have them, in front of you, in a live demo:

  • Build a Cube with Derived Dimensions and a new Report on the Cube on the Spot
    if they can’t do so (in 15 minutes), they are a last generation platform that can only work on pre-defined and pre-built OLAP cubes
  • Run a categorization exercise on at least 3 months of your transaction history / invoice data and at least 100,000 transactions
    if they can’t either use their AI, or powerful (collaborative) filtering and priority based rule definition, and get to the 95% mark in an hour, it’s not for you … (and, trust me, you don’t need AI to get to the 95% mark if the rule definition capability is appropriately defined)
  • Map the cube to a new taxonomy, create new derived dimensions, and create a set of filters that will allow comparison reports to be run between the cubes
    let’s face it, there is no one size fits all taxonomy for analysis, and this is the kicker test to see if the platform can support any taxonomy that is needed, run any analysis you want, and allow you to run comparison reports both as checksums and as differentials to figure out where the opportunities are hidden

All this should take less than a morning or afternoon. But it means the provider deserves to be on your short list.

You Want to Get Cognitive? Then Get Analytical!

As per our post yesterday, the new “cognitive” buzzword is getting a lot of people interested in modern Sourcing and Procurement technology, and that’s a good thing, except when it isn’t. (How can it now be? Not all providers truly offer cognitive capabilities, not all are equal among those that do, and not all are right for your organization.)

And unless you truly understand what cognitive sourcing can do, when it should be used, what technologies you need to power it, and how to properly apply it, the answer is no cognitive sourcing is right for you.

In yesterday’s post, we noted that there were five (deep) technology requirements that a cognitive sourcing platform had to meet to have any hope of truly being cognitive and zeroed in the optimization requirement to indicate that before you even think about getting cognitive you better acquire, and master, strategic sourcing decision optimization because you can’t really properly apply what you don’t really understand, and the vast majority of organizations don’t really have a clue what this is because they don’t have it.

But optimization is not the only area that the average Procurement organization doesn’t have a good grip on. Spend Analytics is another area. Most organizations that have “spend analytics” solutions really have first generation “spend reporting” solutions that are nothing more than a set of canned reports and a few mildly alterable report templates that are customized to certain categories or segments of the supply bases. That’s not analytics.

Regular readers of Sourcing Innovation know that true analytics is the ability to create your own cubes, derive your own dimensions, define your own (pivotable, filterable) reports, and drill across data elements until you find opportunities that cannot be exposed by a canned report. (See the Spend Analysis archives for over a decade of great insights.)

Next generation cognitive systems find opportunities by doing more than just running a set of canned reports on a monthly basis and looking at trends. They are regularly running running variations of dozens, if not hundreds, of analytics on purchase data against deep should cost models populated by ever changing commodity and market costs feeds and looking for variations and emerging trends that could signify potential opportunities as they emerge.

But to understand what’s an emerging opportunity vs. a blip and what is small enough to allow automated platforms to procure and big enough to justify a deep strategic sourcing event or second look at the market, you need to understand just what analytics can do and how to best apply the insight gained from, and the capabilities provided by, a modern cognitive platform — and that requires hands-on experience.

So get a modern spend analytics solution and get your hands dirty in the data. Then maybe, someday soon, you can think about getting cognitive.

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.