Category Archives: Spend Analysis

Spend Analysis II: The Psychology of Analysis

Today I’d like to welcome back Eric Strovink of BIQ (acquired by Opera Solutions, rebranded ElectrifAI( who, as I indicated in part I of this series, is going to be authoring the first part of this series on next generation spend analysis and why it is more than just basic spend visibility. Much, much more!

Data analysis that should be performed is often avoided, because
it carries too much risk for the stakeholder. Let’s consider two examples.

(1) Suppose I am an insurance company CPO with access to one or more
analysts; and that some number of analyst hours are available to me,
in order to investigate savings ideas that occur to me from time to time.

Now, suppose I begin wondering whether the company’s current policy of
auctioning off totaled vehicles is wise. I reason: what if we’re
actually losing money on some of these wrecks? I think: perhaps there
is a closed-form sheet I can provide to my adjusters that lists make/model/year and gives them an auction/no auction decision; perhaps that sheet would save the company money.

My problem is that I’m not entirely sure that this idea is worthwhile.
Perhaps the company makes money on almost every auction, and I will waste the valuable time of one of my analysts by chasing phantom savings that aren’t there. I must weigh not only the cost of the analysts’ time, but also the lost opportunity cost associated with the analyst chasing a low-probability idea — against using that analyst for some immediately useful purpose, such as prettying up a report that the CEO complained about, or double-checking a number for the CFO.

I reason as follows: if I think it’s going to take longer than X hours
to determine whether this is a good idea or not, then I can’t chase the
idea. I don’t have the resources to do so, and perhaps I never will.

However, if I know that my analyst can load up a new spend dataset with
auction costs and revenues within minutes; and I know that a subsequent
slice/dice by make/model/year would be trivial; and I know
that a report of precisely the format I need could be produced without
significant effort; then the decision is a no-brainer. I make the decision
to analyze rather than the decision not to analyze.

(2) Suppose I am a CPO with a large A/P spend data warehouse available to me, but the particular question I want answered is not supported by the dimensions and hierarchies that it contains. Those dimensions and hierarchies were built perhaps by the IT department, or perhaps by a spend analysis vendor, or perhaps by a team of internal support people who are responsible for maintaining the warehouse; and those dimensions and hierarchies were the result of a number of committee decisions that will be difficult to alter. Furthermore, the data warehouse is being used by hundreds of other people in the organization — which means that I’ll need the permission of all those potential users to change or add anything.

I reason as follows: I know it will take weeks, perhaps months to convince
my colleagues to change the dataset organization, even if they can be
convinced to do so; and once they are convinced, it will take even longer
for whomever it is that controls the warehouse to implement the changes, perhaps at high cost that I will need to justify; so is it really worthwhile for me to pursue using the warehouse to answer my question?

I decide: probably not. Which means that my analyst will have to spend many hours extracting raw transactions from the warehouse; re-organizing them herself on her personal computer, using Access or other desktop tools; and then creating the report that I need. As above, I reason as follows: if I think it’s going to take longer than X hours to answer my question, then I’ll live without the answer rather than risk wasting precious analyst cycles.

However, if I know that my analyst can tweak her private copy of the dataset, adding dimensions and changing hierarchies in just a few minutes, and that my answer will be available shortly thereafter, I make the decision to analyze rather than the decision not to analyze.

A flexible and powerful spend analysis system can make a huge psychological
difference to an organization. It changes the analysis playing field
from “we just can’t afford to look into this” to “of course we should
look into this!”

Next installment: Common Sense Cleansing

Spend Analysis I: The Value Curve

Today I’d like to welcome Eric Strovink of BIQ (acquired by Opera Solutions, rebranded ElectrifAI) who, as I indicated in my There’s No Spend Analysis Without the Slice ‘N’ Dice post, is going to be authoring the first part of this series examining what is required for a true spend analysis system, spend analysis 2.0 if you are part of the 2.0 movement, as opposed to just a basic spend visibility system.

Spend Analysis has always suffered from what the late British humorist
Stephen Potter might have called the “So What Diathesis.” In other words,
now that you have your spending loaded and classified, what next? Well,
if you’ve never seen your purchasing data loaded into a spend analysis
system, you’re in for a treat, because you can find savings opportunities
just by drilling around. It’s often that easy — drill around; find
opportunities.

However, once the low-hanging fruit is harvested, which can take
anywhere from 6 to 12 months, the value of the spend analysis system
declines steeply — at which point Mr. Potter’s observation comes home
to roost. As illustrated below, there is a moment at which the cost of
the spend analysis system begins to exceed its ongoing value.

It is shortly after this time that (1) usage of the product drops to low
levels; (2) the rest of the organization begins to question the value of
the software; and (3) stakeholders come under pressure to justify continued
high expenditures.

That’s why it’s odd to hear people talk about “The Spending Cube” —
in capital letters — as though there were only one data cube ever
to be built. Actually, there are many different ways to look at spend,
and there’s lots of spend data that simply can’t be organized into a
single data cube anyway. How about a compliance cube, oriented around
invoice level data? A purchasing card cube, specific to p-card idiosyncrasies?
A T&E cube, built from travel agency data on “best price” versus
“actual price,” tracking employee travel and the reasons for the discrepancies?

In fact, it’s obvious to anyone who has worked with multiple datasets at
the A/P, PO, and invoice level that there are many, many different kinds
of data to analyze. Each dataset addresses more opportunity, and presents
another chance to apply a sophisticated analysis tool. Some of these
datasets aren’t “spending” datasets at all, but consist of demand-side
information — for example, cell phone or fleet vehicle usage records,
or operational data such as equipment recovery and maintenance logs.

If a spend analysis system makes it easy to load data and create new datasets,
which it should; and if the system supports as many datasets as you’d like,
as it ought; then there really isn’t any limit to how often the system can
be used, or to how many different kinds of data it can be applied. Which
means that a full-utilization spend analysis system value curve looks more
like this:

In other words, each use of the spend analysis system provides high
initial value, as well as residual value; but the system is used again
and again for new sets of data. The value of the spend analysis
software therefore remains high over time.

Next installment: The Psychology of Spend Analysis

There’s No Spend Analysis without the Slice ‘N’ Dice

When I was in Boston, I was lucky enough to spend the better part of the day with Eric Strovink of BIQ, and have a few extended conversations with individuals at some of the local consulting firms that specialize in sourcing, and am now more than convinced that any tool that mandates a single cube, or makes it difficult to change the cube, is not a spend analysis tool, merely a spend data warehouse with built in canned reporting (and, if you’re really lucky, limited ad-hoc capabilities).

Not that there’s anything wrong with a centralized spend warehouse with a consistent view of your total spend, especially one that integrates multiple internal and external data sources and allows you to drill down and understand your spend at a detailed level. Of all the e-Sourcing software tools, it is the one most likely to make your CFO do backflips, especially if it has good reporting (and this is a big if – not all spend analysis tools on the market do), since it makes it really easy for the CFO to tell the CEO where the money is going and comply with all those pesky reporting requirements.

However, the value of such a tool is quite limited to you as a purchasing agent. Now, it’s true that the first time you’ll use it you’ll save big-time, especially if it’s the first time you have visibility into the majority of your spend, but the reality is that this is the only time you’ll see such significant savings. After you’ve identified all of the low hanging fruit identified by the single view provided to you by the system, analyzed each instance of over-spending, and taken corrective actions, you’ll find that you’ll be unable to identify additional savings and the system will simply function as a glorified data warehouse that you only use once a quarter to create those reports for your CFO and check that your teammates our buying off the negotiated contracts – something that you could do almost as well with your existing ERP system and a significantly cheaper Business Intelligence / OLAP tool like Business Objects or COGNOS and some grunt work.

Remember, I’m not saying that traditional spend analysis systems like those provided by e-Sourcing providers like Procuri (acquired by Ariba, acquired by SAP) and Emptoris (acquired by IBM, sunset in 2017) are not without value – if you do not have a good, integrated, data warehouse that integrates your various accounting, purchasing, and inventory systems to provide you a single view of your spend or a good reporting system to produce all of the reports your CFO needs, then you’ll find these systems very valuable. However, it’s important that you understand that the primary value of these systems is in the total spend visibility they provide from a financial viewpoint, not the spend analysis capability you really require to identify potential overspending and cut-costs, because you’ll only be able to do this once – thanks to the single organizational view they are built on. (In other words, you’ll save big when you fist implement the system but future savings will be limited to your capability to quickly catch and stop maverick spend.) So, if you need a system to consolidate your spend data, produce the tedious reports required by all of the new financial reporting requirements, and give you some basic across-the-board spend visibility, or, more importantly, you need a spend data warehouse that integrates with the rest of your e-Sourcing suite, be sure to check these systems out – but understand what they are really worth to you before you sign the check.

In order to help you understand where these systems fail in true spend-analysis, why you need to be able to dynamically create multiple cubes on the fly which support dynamic dimensions, meta-aggregation, cross-dimensional roll-ups, and even federated data sets, I’m happy to inform you that Eric Strovink has agreed to co-author a series of posts outlining what real spend analysis is, how it differs from basic spend visibility, what it does for you, and why you need to get there. Stay tuned. (This series is bound to be as informative as my CombineNet series which, when combined with Paul’s informative posts and rebuttals, is probably one of the best non-marketing filtered sources of information out there on decision optimization.)

On the Ninth Day of X-Mas (Emptoris vs. BIQ)

On the ninth day of X-Mas
my blogger gave to me
spend vendors lancing,
thoughts for a shilling,
strategies for winning,
tactics for saving,
five golden rings,
four little words,
tri-focal lens,
two boxing gloves,
and a lesson in strategy.

In this corner, hailing from Burlington, at a whopping 800 lbs, the heavyweight champion of the space, Emptoris (acquired by IBM, sunset in 2017) and in this corner, hailing from Southborough, at a lean and mean 200 lbs, the lightweight contender, BIQ (acquired by Opera Solutions, rebranded ElectrifAI).

Amidst a flurry of Much-Ado-About-Something, all started by a few innocuous postings over on Spend Matters in the month of Shimo tsuki, the spend visibility debate has been kicked into sixth speed maximum overdrive as the result of an all-out-melee sure to satisfy even the most staunch of Stephen King fans. Even my declarative proclamation that Spend Matters Not!, as a rebuttal to my inquiry as to whether or not Spend Matters Most? has been lost in the virtual mortar fire between Emptoris and BIQ’s legal quests to prove that the pen is indeed mightier than the sword.

Emptoris, the apparent Victor Von Doom of the Spend-Analysis-Driven-Intelligent-Savings-Targets mindset, or S.A.D.I.S.T, has the most extensive offering of any contender on the playing field, with its various spend data manager, real time classifier, spend analyzer, data enrichment, and reporting engines which combined appear to provide more raw power than the Human Torch, the Thing, the Invisible Woman, and Mr. Fantastic put together. In comparison, BIQ, your friendly neighborhood Spiderman, is clinging to the field with its single Veg-O-Matic offering (It Slices! It Dices!) and its unique Meta-aggregation-Shifting-of-Classification-Hierarchies-in-Subsecond-Time capability, or M.a.S.o.C.H.i.S.T., which has me singing the praises of Mr. Popeil.

Both have their virtues. Emptoris is probably the only solution that can allow you to analyze not only your relative spend internally, but relative spend against the rest of the market – and maybe help you break through the curse of those rose colored glasses normally worn by your executives. In comparison, BIQ is probably the only solution that can allow a buyer to look at her data any way she wants to, at any time, allowing her to find and exploit hidden relationships with its transmutative engine, helping her break out of The Metamorphosis she will someday awake to find herself in without it.

Both have their failings. The S.A.D.I.S.T. view of the world is a single view from within the walls of a single, but complete, cube, boxing you in to one vision of the world. In comparison, the M.a.S.o.C.H.i.S.T. view, borrowing a piece of technology from The Guide, Mark II permits you an infinite number of views of the world, with the caveat that they are all potentially incomplete. In short, if you asked mirror-mirror-on-the-wall, who’s the fairest of them all, I would be tempted to say that even he would not be able to answer you. The fact of the matter is, for all you techies out there, (and maybe even a few of you Trekkies), that while Emptoris wins on breadth of solution, BIQ wins on depth, and the best single solution for you depends on your view of the world and the best solution overall is probably the adoption of both types of solution. The single world view to please your executives who like to stare into space with their rose coloured glass intact and the changing world view for your sourcerers to gain the insight they need to make better buys.

But all I can say, is when it comes to legal sparring between two obviously different solutions, even though they both exist on the same coin, is the offing was barred by a black bank of clouds, and the tranquil water-way leading to the uttermost ends of the earth flowed somber under an overcast sky. For if the fight continues, only Wolfram and Hart will win in the end.

For those of you who want to review the debate-to-date, here is a brief history in time:
“Spend Management and M&A”*, Spend Matters [WayBackMachine], (Nov 3, 2006)
“It’s Only the Beginning for Spend Visibility and Analytics Growth”*, Spend Matters (Nov 17, 2006)
“Emptoris: Readying the Spend Visibility Armaments for Battle”*, Spend Matters (Nov 28, 2006)
“A Spend Visibility Smack-Down”*, Spend Matters (Nov 30, 2006)
“Ariba: Not Sitting Still in the Spend Visibility Arms Race”*, Spend Matters (Dec 1, 2006)
“Spend Visibility Gets Legal: Emptoris vs. BIQ”*, Spend Matters (Dec 5, 2006)
“BIQ Respond to Emptoris’ Lawsuit”*, Spend Matters (Dec 6, 2006)
“Sourcing Innovation Adds to the Spend Visibility Controversy”*, Spend Matters (Dec 11, 2006)
“Emptoris: Blurring the Legal and Marketing Line”*, Spend Matters (Dec 12, 2006)
“What is the ROI of Spend Visibility and Analysis Solutions?”*, Spend Matters (Dec 13, 2006)

Merry Christmas Spend Fool!

* All posts prior to 2012 were removed in the Spend Matters site refresh in June, 2023.

Spend Matters Not

Not long ago, sometime after my post where I asked Is it the Case that Spend Matters Most?, the posts “Emptoris: Readying the Spend Visibility Armaments for Battle”* and “Ariba: Not Sitting Still in the Spend Visibility Arms Race”* appeared on Spend Matters and generated quite a buzz. I’m now convinced that most of the providers still have not progressed beyond Spend Analysis 1.0 and, more importantly, that spend, or at least the amount of spend, doesn’t matter.

It’s not how much you spend, how you store it, how you cube it, or how you report on it – it’s how much you get, how you profit from it, and how you improve on it. It’s all about value, profit, and continual improvement. The fact of the matter is, sometimes spending more is the right thing to do. If you’re spending more to build higher quality products that allow you to double your profit margins and drastically increase revenue, compared to spending less, building the same products, and having your profit margins shrink to nil because they are not innovative and desirable compared to the rest of the products on the market, then you’ve made the right choice. Just like you should focus on Total Value Management, and not Total Cost of Ownership, when you make your award decisions, you shouldn’t be focused on how much you’re spending when doing spend analysis. It’s what you are spending it on, who you are buying from, the prices you are paying relative to the prices you could be paying and the rest of the market, and opportunities you have to drive value from the spend.

So, how do you figure this out? Analysis. Flexible, powerful analysis that allows you to aggregate, slice and dice, associate, break-out, normalize, aggregate, and slice-and-dice again. Analysis that allows you as the user to see the data any way you want to see it, any time you want to see it, any how you want to see it. A rigid view on a fixed set of dimensions might tell you that you’re spending 30% more on supplier X, but it might not tell you that you’re spending 60% more on servers, 10% more on workstations, and 10% less on laptops compared to other suppliers. In other words, a rigid cube analysis might lead you to conclude that you should be dropping supplier X for suppliers Y and Z, when really you should only be dropping them as a server supplier, aggressively negotiating with them on workstation pricing, and routing more laptop purchases through them for a larger discount.

I have to agree with Eric (Strovink) of biq (acquired by Opera Solutions, rebranded ElectrifAI). It’s the analysis. The value added services, especially those provided by Emptoris (acquired by IBM, sunset in 2017) in their new release, are great, and they can be used to create some top notch reports that will knock the socks off of your stodgy old CFO, especially compared to what you can pull out of a traditional ERP, but that’s not how you drive maximum performance. Drop the spend. Focus on the value. Which supplier is giving you the highest value ratio (the most quality product for the least spend)? On which categories? Why? Which categories are performing the worst? On which categories? Why? Which suppliers do you have multiple contracts which? Any way to leverage the volume? And so on. You need to be able to build a cube, analyze it, slice off dimensions, extract a sub-cube, aggregate the data, run a report, and then compare it to a report generated off of another sub-cube for a different, but complementary, data set.

After all, it all comes down to the bottom line. It’s not what you spend. It’s not the revenue you take in. It’s not your operating costs. It’s how much profit the business makes at the end of the day and the value it returns to its shareholders. And that requires smart spend management based on actionable intelligence – the kind enabled by next generation spend analysis and visibility solutions. Everything else is just reporting – sometimes really, really, really good reporting – but just reporting.

And if the user can’t hack it … then the user needs to be trained or be replaced. Commodity prices are going up. After the third reverse auction, there’s no more fat left to trim. Once you’ve implemented the latest IT system, there’s little room for productivity improvements. That simply leaves collaboration, innovation, and smart spend management.

On a side note, I applaud Iasta for basing their new spend analysis solution on BIQ’s solution instead of trying to build their own from scratch. It takes years to build a good spend analysis solution, and since they are on-demand, they can easily integrate BIQ’s on-demand solution into their platform and extend it with value added services, which is where the real value is. This complements their core strength, the executable sourcing cycle, with a SaaS solution that helps the user determine the best category candidates for dedicated eSourcing events. Furthermore, as time progresses, they can build up baseline cubes and reports for common categories to jump-start the process for new customers and junior analysts. And, since it’s a partnership and not an acquisition, you don’t have one company swallowing another. Although this sounds great in principle, what usually happens is that the development teams merge, the new blended company adopts “one focus”, and a lot of the distinctive expertise that made the acquired company the best at what they do gets masked or disappears. BIQ is going to continue to build a better, differentiated, spend analysis product, Iasta is going to continue to develop better services around the product for the sourcing professionals it serves with its end-to-end executable eSourcing suite, and everyone is going to win. The only thing keeping it from being a perfect solution is the ability to easily integrate 3rd party data sources for spend augmentation and market-based reporting. But I’m sure that will come in time.

* All posts prior to 2012 were removed in the Spend Matters site refresh in June, 2023.