Category Archives: contract management

Contract Compliance Trust But Verify: Part III Monitoring Demand

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.

When you join transaction data to contract data in order to validate contract price compliance, it is possible to discover lots of interesting information. Some if it can be quite surprising.

For example, you might notice that off-contract items make up a surprisingly large proportion of the spending. This may be trending up with time, so it is worth doing a time-series analysis. You might also notice a pattern of overcharges on particular items, which could be an easily-corrected disconnect at the vendor side on contract terms.

In Excel, these analyses require new pivot tables and, concomitantly, more maintenance effort on refresh. But in a spend analysis system, the model can be augmented with additional pivot-table-equivalents in seconds, with just a few mouse clicks. And, refresh is not an issue, because the spend analysis system updates everything automatically upon loading new transactions. So, much more interesting analyses become real possibilities — including monitoring demand.

The Who

Suppose that we have from the vendor not only the item pricing, but also an idea of who within the organization is doing the purchasing. This then enables us not only to identify off-contract spending, but also find the source of the leakage within the organization, so that corrective action can be taken internally.

There are a number of ways that “Who bought the items” can find its way into PxQ data. Sometimes it is present as a matter of course; sometimes it requires effort.

  • If the item is a catalog buy or punch-out, invoice items likely already contain the cost center.
  • If a PO number was provided to the vendor, invoice items should contain the PO. The PO can be easily translated to cost center (well, “easily” if the PO data can be linked in, as it can be with a spend analysis system).
  • If there’s a useful delivery address on the invoice, that can be mapped to a cost center using the spend analysis system’s mapping tools (of course, you need access to the mapping tools, and they need to be simple to use).
  • Your contract with the vendor could require a cost center to be provided on the invoice as a prerequisite for payment. No cost center, no payment.
  • Corporate purchasing cards are by definition associated with a cost center, so these can be mapped to cost center using the spend analysis system’s mapping tools.
  • Consultants put project codes on invoices; lawyers put matter numbers. These can be mapped to cost centers as well. Any invoice without a project code or matter number shouldn’t be paid.
  • Some spend already has a fixed cost center, for example with copiers. Each copier is assigned a cost center, which shows up on the invoice.

In a nutshell, if you want to have a cost center attached to each row of an invoice, it is very doable, and very worthwhile.

Let’s revisit the dashboard from Part II.

  • We can see a breakdown of overcharge buys by cost center (blue). A similar breakdown of off-contract items helps identify who is buying off-contract. There may be very good reasons for this, of course; and those reasons need to be understood, so that we can either get those items onto the contract, or channel the buying to similar items that are on contract.
  • We can see a time-series analysis of item buys by class, with an associated chart (red). Over time, fewer items are being bought with the contract price, which is not a good trend.
  • We can see all the buys, showing both contract and overcharged prices (green). This is all we need to show to the vendor — just dump it to Excel, email the spreadsheet, done.

Click to enlarge

The basic pattern of this type of analysis doesn’t change with the commodity. Providing that the goods or services can be standardized with a fixed price, and that a contract price is available, the technique is always the same — and the analysis always worthwhile, if only to prove that the contract is in place and actually working.

Thanks, Eric!

Contract Compliance Trust But Verify Part II: Monitoring the Vendor

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, you should be paying the contract price. But until you check, you don’t really know — and what you find out may surprise you.

In Part I of this series we discussed the two pieces of data required — transactions from the vendor, and contract prices for the items under contract. The next step is to join those two datasets together, in this case by Part Number.

Here is what that might look like if we do it in Excel:

This was done by:

  • Sorting the contract prices by Part Number so VLOOKUP will work
  • Building a helper column K which is the difference between invoice price and VLOOKUP’d contract price (hidden)
  • Building a VLOOKUP to compare contract price to invoice price (shown)
  • Building a Pivot Table to roll up column L

Lots more could be done. For example, we could:

  • Add a computation of the amount of overcharge.
  • Add year-month to the pivot table, giving us an idea as to the distribution of the overcharges. Have they all occurred recently, or just in the relatively distant past?
  • Produce a table of only the overcharged items, in order to send it to the vendor with a request for compensation.
  • Identify “who” is buying the excluded items (more on this in Part III).

However, as the model becomes more complex, it becomes more difficult to maintain. What happens next month, when a new tranche of transactions is available? Who updates the model? Each of the formulas and pivot tables needs to be updated carefully — a process that’s irritating and time-consuming at best, as well as highly error-prone.

Make it Easy, not Hard

A spend analysis tool can make this a lot easier. Load the two datasets, and link them by Product Number. Then build a price difference column, set up a range, and you’re done. This requires no advanced Excel knowledge, and produces a model that updates automatically when new data are added. This dashboard was put together using Spendata, but there are certainly other options.

Click to enlarge

And now, adding next month’s data to the analysis is anticlimactic — literally a couple of clicks, and everything auto-updates. So, even if you could “do it in Excel”, you won’t, because it’s just too painful. But if you use the right tools, you can produce compliance models quickly, and you can maintain them with near-zero effort.

We’ll conclude our discussion in Part III: Monitoring Demand. Thanks, Eric!

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.

Time for Spring Cleaning. Start With Your Evergreen Contracts.

The spring tradition is to clean house, and that means your house of business as well. Chances are there a number of areas of your operation that need to be cleaned up, but the place to start is your evergreen contracts. Most organizations have significant overspend in these contracts because prices have dropped, demand has increased, and/or new options have entered the market — but since the organization decided to set, and forget, these contracts, it has not been able to take advantage of new options, negotiate against the increased demand, or realize the reduced prices.

So how do you start?

First, make sure all of your contracts are in electronic form and in a central electronic filing cabinet.

How do you do this?

Acquire a good OCR solution and feed all your paper contracts through it and create a set of contract e-documents.

Then, acquire a good network drive scanner to find all of your e-contracts. Some might be part of the scanned set (as they were printed out and filed), some might be duplicates (as different users might put them on different drives), and some might be draft versions.

Finally, to get a complete (as you can) distinct set of contracts, run them through a semantic process that can identify similar documents that will group all documents that are highly similar into a set and identify the (likely) final version based on dates (and differences between similar documents).

Then, figure out which contracts are, or could become, evergreen …

How do you do this?

Acquire and apply a semantic analytic solution that can sift through the contract clauses, identify the term, and whether or not the contract is, or could become, evergreen.

… and order them by upcoming (auto) renewal date.

This is just a simple sort, which can be done by exporting the contract titles and (auto) renewal dates to a spreadsheet which is easily sorted.

Then do a spend analysis (and projection) on each category defined by the contracts, in (auto) renewal order, and when the savings percentage is significant (near double digits) or the savings amount is significant (many 3X to 5X times what a category re-sourcing would cost), provided there is enough time to re-source, you queue up the sourcing event. If there is not enough savings potential, or time, you add it to the end of the queue to be reanalyzed sufficiently in advance of the next auto-renewal date.

Eventually you’ll work your way through all the evergreen contracts, and replace them (with non-evergreen contracts) in order of priority, defined by savings potential.

And that’s how you start your evergreen contract spring cleaning.

Trade is Getting Complicated. Trade Agreements More So. Are Your Contracts Up to Snuff?

It’s difficult enough to create contracts that specify what both parties want, but with the shifting global landscape, crumbling trade agreements, new ones rising to take their place, and new regulations cropping up all the time that companies need to adhere to just to do business in their home country, it’s almost impossible.

How do you define contracts that keep up? And, more importantly, how do you figure out which of your contracts are not up to par, and where they are falling short?

In the first case, you constantly monitor government sites, associations, and news sites for mention of new regulations and requirements to adhere to them. Then you process the news, make sense of the new requirements, and find some experts to help you understand the best way to contractually deal with the new rules.

In the second case, you need to be able to quickly analyze a contract and determine if there are clauses to address the regulations. But if it’s a 50 page contract, that’s not a quick effort. And if you have 1,000 of them? 10,000 of them? How can you even attempt to do that?

Manually, you can’t. You need tech that can identify which contracts are likely lacking one or more clauses to address one or more regulations and bring them to your attention, in order of priority. Advanced, semantic, technology that can understand documents, deficiencies, and suggest potential fixes.

And a few companies understand that, and that’s why you see the likes of companies like LawGeex and LegalSifter rising up to challenge Seal with a new take on contract analytics and the need for. Because, one way or another, once you reach a certain point on your sourcing journey, you’re going to need this technology.