Category Archives: Spend Analysis

Opportunity Analysis: The Challenge is Having Accurate and Usable Spend Information

Today’s guest post is from Bernard Gunther of Lexington Analytics.
He can be reached at bgunther <at> lexingtonanalytics <dot> com.

Sourcing Innovation‘s “Seven Grand Challenges for Supply & Spend Management“, lists the seventh challenge as “Opportunity Analysis”. As a practitioner, I can report that bad procurement data is the biggest obstacle to successful opportunity analysis. By “bad” I mean procurement data that exists when the items are purchased / invoiced is not captured and made available for future analysis. The ongoing data analysis is rarely designed into the procurement process making the analysis hard to do and therefore rarely done.

I find it surprising that half of the large companies I deal with don’t have a formal process for analyzing their AP data. Though they may dump transactions from their AP system into a spreadsheet or a data warehouse, the data is raw and unprocessed and not consistently analyzed or well understood. This is not proper spend analysis, it is flying blind. If the quality of procurement information is so lacking for AP data — the most basic spend data — imagine how bad it is for invoice level data where pricing accuracy can be determined

Accurate and usable procurement information requires source transaction data, ways to enhance that data, and processes to get value from the enhanced source data. The data should be collected and analyzed as part of the regular purchasing process. Data analysis should be designed into the process flows. I will illustrate some of what’s involved to answer the simple question, “Did I pay the right price for an item?”

At a high level, the source data includes:

  1. “Transaction level” information on each purchase that includes: what is purchased, the unit pricing, the amount bought, who bought it, and data to link each transaction to the order, the payment and the contract. The specific data available will vary depending on the commodity. Airline information is different than computers, which is also different than facilities management.
  2. Contract information structured so that each item on every invoice can be priced and stored in a way that links them to transactions.
  3. Payment information which identifies the vendor being paid, who bought the item, which transaction detail links to the payment.

Data Enhancement: Making the raw data meaningful.

  1. Commodity assignment. For an item level cube, the commodity assignment will be more detailed than an AP cube and may be based on the description, the part number, or other attributes of the item.
  2. Pricing context. Each item purchased should link to the contract price, historical pricing, benchmark pricing (internal and external), and other information that puts the unit price paid into context.
  3. Cross item information. Some of the pricing comparisons need to be done across multiple items rather than against a single item. An analysis of the mix of team members on a consulting engagement or a legal matter would be an example.

Data Processing: Converting the meaningful data into actions that save money.

  1. Every month or quarter, the data needs to be collected, enhanced, and analyzed. The analysis should be able to answer such as:
    • Did we pay the contract price?
    • How much of the spending was off-contract?
    • How did the demand shift?
    • How much of the spending was on items that were not intended to be purchased?
    • Which organizations are responsible?
    • How much extra spending did this cause?

    Each company should be able to answer these basic questions in hours, not days or weeks. The data should be in-house and it should not require work from the vendor beyond originally providing the data as part of the invoicing process.

  2. Periodically, the team needs to answer questions like:
    • For a recent price change, what happened to the spending? If we applied the old pricing to the new spending pattern, how much would we have spent? Is this what was expected?
    • Is the mix of items we buy “optimal”? How much could we save by optimizing our demand?
    • How has the market price changed relative to our pricing? Is there enough shift that we should re-bid our spending?
  3. Use the data to generate savings, for example:
    • Request refunds for overcharges
    • Add more items to the contractual pricing terms so we can monitor the pricing moving forward
    • Shift the demand to generate savings
    • Negotiate with the vendor for lower prices

    And, on and on for different ways to leverage the information

This all sounds relatively easy. But it’s not happening today. Let me illustrate from a client example of office supplies. I don’t mean to pick on office supplies vendors, but this is a category with part numbers and contracts so it provides a good starting point for this type of analysis.

The client bought office supplies online through a punch out mechanism from their PO system. The vendor processes the orders, ships the items, and presents invoices for payment. The invoices are approved in the PO system and the vendor is paid per the contract. The contract was written 2 years ago and allowed for fixed (discounted) prices for the top 500 items being bought. When the contract was signed, 250 items were on the list. The new contract offered price reductions on certain items, which the sourcing team projected, would save 12%. Since the contract signing, most prices have been stable, with some exceptions for paper.

As the program was implemented by the client, there were a number of problems with the data:

  • For 20% of the items purchased, the item numbers recorded in the PO system did not match the item numbers in the contract. This was largely a problem of how the PO system recorded the data
  • The client could not state what percentage of the spending was for items with contract prices and what percentage was off-contract. The client needed to ask the vendor for this analysis.
  • The client had agreed to price changes, but did not track those changes and could not calculate the impact of those price changes on overall spending. Again, they had to rely on the vendor to track the pricing and do the analysis.
  • The buyers had shifted their demand, so that of the 250 items in the contract, over 75 were not being bought anymore and of the top 250 items being bought, there was no contractual price for almost 100 of the items. The vendor was waiting for authorization to add 50 new items onto the contract list (with better discounts).

This was all fixable. Fixing it generated incremental savings of 5% and improved the relationship between the client and the supplier. But it didn’t happen until we, the consultants, highlighted the problem and the opportunity.

Generally, we find that procurement data is a mess. And it shouldn’t be. But, this is why it’s a challenge.

Thanks Bernard!

the doctor’s Seven Grand Challenges for Supply & Spend Management

Seven deadly sins
Seven ways to win
Seven holy paths to hell
And your trip begins

Seven downward slopes
Seven bloodied hopes
Seven are your burning fires
Seven your desires….
  Adrian Smith / Bruce Dickinson

In my last post, which announced the cross-blog series that this post is officially kicking off, I reviewed the seven grand challenges for IT over the next twenty-five years, as laid out by Gartner back in the spring. Although they ranged from the ridiculous to the sublime, and contained a fair amount of overlap when closely analyzed, it’s a worthwhile exercise to undertake every now and again, because in order to develop a useful solution, you need to identify what is needed and the path you should be on.

This inspired me to propose a set of “seven grand challenges” for supply and spend management, in the hopes that it would get you, dear reader, to think about what is important, what problems should be solved, and where we should go. Considering how important supply management is in these troubled times, I hope that all of my fellow bloggers chime in with their ideas on what’s good, what’s bad, and, what’s downright ugly in supply chain today — because the first step in solving a problem is properly identifying it.

So, without further ado, to kick off this cross-blog series, here are the doctor‘s proposals for the seven grand supply and spend management challenges:

  • Optimization
    There are a number of challenges here. The first challenge is getting people to use solutions that are already out there. There are currently a number of offerings that address strategic sourcing decision optimization, distribution network optimization, and freight optimization quite well, and that, when properly applied, can save the average company up to 12% above and beyond the best solution obtained with auctions. The second challenge is integrating the different problems (sourcing optimization, freight optimization, network optimization, etc.) into a common framework that allows the tradeoff effects of each decision to be adequately modeled and understood in the big picture. The third problem is addressing the emerging non-quantitative regulatory and compliance requirements such as RoHS, WEEE, and GHG emission limits in a consistent and value-oriented manner within the optimization model.
  • Supplier Enablement
    This is something we still don’t have a good handle on. Beyond “supplier enablement is the provision of technology based solutions that enable the supplier to be more productive and better serve the buyer”, there isn’t yet a general consensus of what this technology needs to be, as most companies have not yet embraced B2B 3.0. I’ve argued before that, today, it’s a combination of catalogs, networks, e-Document exchange and management, and supplier portal technology, and I still think that is a good start, but enablement should go beyond enabling the exchange of information, it should improve the supplier’s operations overall.
  • Integration of the Physical, Information, & Financial Chains
    For most companies, these are three different chains. Some companies that have embraced RFID, GPS, and e-document management have taken the first steps to integrating the physical and information flows, but the technology is still emerging, the integration isn’t smooth without extensive integration and customization between a number of different solutions (and only Fortune 500 companies can even afford to consider this), and we have only started to look at the financial supply chain and how to best integrate it with the information supply chain. I think it will be a while before solutions that truly support a holistic view will emerge, especially considering that even the gorillas in the space don’t have end-to-end sourcing and procurement.
  • Solution Globalization
    Let’s face it … supply chains today are truly global, but the solutions are not. Most “internationalized” solutions are only available in a smattering of languages, most “internationalized” solutions are not plugged into real-time currency exchange feeds — and few developers have thought about the need to maintain/display multiple conversions (including the rate at the time of purchase, the projected rate, the current rate, etc.), and most “internationalized” solutions don’t help you understand how to do business with the country of interest.
  • GHG Tracking and Reduction
    Most enlightened countries have woken up to the fact that, even though we don’t know precisely how damaging each ton of GHG and / or carbon we emit is, we do know that it’s damaging and that we have to reduce our emissions. The first step is to get a baseline of the emissions produced by your operations, but for many companies, this is a multi-year effort. Better product and service solutions are needed. Also, although there are multiple proposals on the table to reduce emissions, there are few total value management models out there to help us select the right ones.
  • Risk Prevention
    Not only is risk not going away, but it’s getting worse by the year. Supply chains are getting more complex by the year, and the likelihood of something going wrong is steadily increasing. Solutions that can help a company identify risks, in real time, and identify possible mitigations and actions required to implement them, are desperately needed.
  • Opportunity Analysis
    Costs are skyrocketing, but consumer discretionary spending is stagnant at best. They key to a successful supply chain is cost reduction and avoidance, and this requires continual opportunity analysis. I envision this starting with modern spend analysis, but it needs to go beyond true spend analysis to continual innovation, since the greatest cost reductions will come from true revolutions, and not just the shrewd identification of category-based overspending. I envision that this will start with the integration of PLM with Life Cycle Analysis and Next Generation Analytics and then morph into something that none of us can envision today.

Now, I realize that these are pretty much the same problems we have been facing for the last five to ten years, but I suspect that it will be quite a while before they are solved due to the overwhelming complexity of today’s supply chains.

When the series is done, I’ll compile the “master list” of challenges and, if any of my fellow bloggers can convince me there are bigger challenges out there, revise my list.

Supply Chain Digest’s Eight Step Forecasting Process Using Demand Planning Software

Every now and again I like to address the forecasting process because, as a sourcing and procurement professional, you are often negotiating contracts against a perceived volume leverage based as much off of a forecast as it is based on historical data. In Part I we reviewed judgmental and statistical forecasts and explained why you need to balance both methodologies when generating your forecast, in Part II we addressed commodities forecasting and how you need to base it on the right data and the right factors, and in Part III I directed you to “Forecast Less and Get Better Results” on SupplyChain.com that demonstrated that the conventional wisdom that companies need to project forecasts and plans far into the future at a highly granular level is not necessarily right. Then, in Forecast with Foresight, I pointed you to a Supply & Demand Chain Executive article on a study about “re-thinking demand management” that noted that active/predictive demand management is necessary for good forecasting.

Part of active/predictive demand management is good demand planning. Good demand planning involves good demand planning software, so it was nice to see the Supply Chain Digest editorial staff print a short guide on how to attack the process, even if the first two steps didn’t fully address the problem.

The process, which was still quite good, that they presented was:

  1. Load Historical Data and Create Master Data
    Identify the key data elements that need to be considered and load them.
  2. Clean the Historical Data
    There are almost always problems with the quality and completeness of the data loaded into the system. E.g. “demand” may not be true demand, because it is taken from “sales” data, and will not include “stock-outs”.
  3. Generate a Statistical Forecast for Existing Products
    Use demand planning software with built in statistical models to find a “best fit” that will give you a starting forecast.
  4. Prepare Forecasts for New Product Introductions (NPI)
    Use the demand planning software to identify products with similar sales trajectories which will be used as the starting forecasts for the NPIs.
  5. Override Statistical Forecasts with Judgmental Input
    Use data from sales channels, knowledge about changes in market conditions, and expert insight to smooth the forecasts into the most realistic forecasts possible.
  6. Adjust the Baseline Forecasts for Promotions
    In certain industries, like consumer goods, promotions can have a huge impact on sales volume and need to be factored into the baseline forecasts.
  7. Manage Vendor Managed Inventory (VMI) and Collaborative Planning, Forecasting and Replenishment (CPFR) Processes
    Be sure to communicate data to both customers and internal managers responsible for these programs.
  8. Generate a “One Number” Forecast
    Integrate forecasting into a Sales and Operations Planning (S&OP) that brings together executives from key areas of the company to ultimately agree on a single forecast number and execution plan that will drive both the demand and supply sides of the enterprise.

The one change I’d make would be to replace the first two steps with the following:

  1. Do a Spend Analysis
    A spend analysis project, performed by a spend analysis expert that uses a real spend analysis tool, will load all of your relevant data, cleanse it, normalize it, and properly classify it in multiple spend cubes. The resulting cubes will allow you to perform the analyses necessary to identify which data is relevant, which data is statistically significant, and, more importantly, which products require significant forecasting efforts and which products are relatively stable year after year. Products with relatively stable sales do not need significant forecasting efforts, because expected demand can be easily determined from the spend analysis. On the other hand, products with variable sales, especially those products with a seasonal demand that are heavily influenced both by manufacturer promotions and competitor’s promotions for similar products, require detailed forecasting efforts.
  2. Load the Relevant Data
    Once you have identified those products that require forecasting efforts, you can load the associated data that is needed to run the statistical models, to determine the effects of planned promotions, and determine the appropriate demand forecasts.

The Vendor in Black (Repost)

The sun did not shine.
We had no time for play.
So we sat in the office.
On that dark, stormy day.

I sat there with Sally.
We sat there, we two.
And I said, “How I wish
We had good tools to use!”

We’re deep in the red.
Our paychecks are stale.
So we sat in the office.
And tried not to wail.

So all we could do was to
Sit!
Sit!
Sit!
Sit!
And we did not like it.
Not one little bit.

>BUMP!<
And then
something went BUMP!
How that bump made us jump!

We looked!
Then we saw him step in on the mat!
We looked!
And we saw him!
The Vendor in Black!
And he said to us,
“Why do you sit there like that?”
I know you are broke
And your paychecks are flat
But we can find
Savings to tuck under your hat.”

“I have some tools that you can use,”
Said the Vendor.
“I have some new tricks,”
Said the Vendor in Black.
“A lot of good tricks
I will show them to you
Your boss
Will not mind at all if I do.”

Then Sally and I
Did not know what to say.
Our boss was out of the office
For the day.

But Diligence said, “No!, No!
Make that vendor stand by!
Tell that Vendor in Black
You do NOT want to try.
He should not be here.
He should not be about.
He should not be here
When our boss is out!”

“Now! Now! Have no fear.
Have no fear!” said the Vendor.
“My tricks are not bad,”
Said the Vendor in Black.
“Why, we can find
lots of savings, if we try
with a report that I call
vendor-GL_code drive by!”

“Please get out!” said Diligence.
“This strikes me as void!
Please get out! said Diligence.
I do NOT wish to be unemployed!”

“Have no fear!” said the Vendor.
“My tool will always work.
It will find you savings
Wherever they lurk.
With a click of a button.
And your ERP app.
It will find you savings!”
Said the Vendor in Black.

“Look at it!
Look at it now!” said the Vendor in Black.
“It’s finding you savings.
To tuck under your hat.
It’s comparison report.
Can handle two divisions.
Broken down by category.
Into subdivisions.
And look!
Pie chart comparisons for one and for all!
But that is not all!
Oh, no.
That is not all … ”

“Look at it!
Look at it!
Look at it now!
It can handle AP data,
with the module that knows how.
It doesn’t cost much more.
Than the basic module costs.
But it’s worth the price.
To prevent savings loss!
And with extra reports.
Your savings explode.
You’ll find hidden treasure.
With that extra code.
Don’t fear the price tag.
It’s a nominal fee.
You heard me clear.
Have no fear!
Just a nominal fee!”

That is what the vendor said.
Then he fell on his head!
He came down with a bump!
From up there high on the wall.
And Sally and I,
We saw ALL our prospects fall!

And Diligence he gloated.
While grinning he did.
He sad, “Did I not tell you?”
Oh, yes! I sure did!
This was not a good game,”
said Diligence in a fit.
“No, I did not like it,
Not one little bit!”

“Now look what you did!”
Said Diligence to the Vendor in Black!
“Now look at this mess!
Look at this! Look at that!
You took all our money.
Sank us deep in the red.
You made us false promises.
Then you fell on your head.
You SHOULD NOT be here.
When our boss is gone out.
You get out of this office!”
Said Diligence with clout!

“But I like to be here.
Oh, I like it quite a bit!”
Said the Vendor in Black
To Diligence with wit.
“I will NOT go away.
I do NOT wish to roam!
And so,” said the Vendor in Black,
“So,
so
so …
I will show you
Another module you should own!”

And then he ran out,
And, then, fast as a fox,
The Vendor in Black
Came back in with a box.
A shiny blue box.
It was sealed with red tape.
“Now look at this,”
Said the Vendor.
“Take a look!”

Then he climbed on the soapbox.
And with a tip of his hat.
“I call this module Enhanced-Data-Blocks,”
Said the Vendor.
“In this box, two CDs.
I will load for you now.
You will like these apps,”
Said the Vendor with a bow.

“I will unseal the tape.
You will see something new.
Two apps. And I call them
App One and App Two.
These two apps will not hassle you.
They integrate well.”
Then, out of the box
came CDS for App One and App Two!
He installed them at once.
Then said, “They’re ready to use.
Would you like to try out
App One and App Two?”

And Sally and I
Did not know what to do.
So we decided to try out
App One and App Two.
We loaded them both.
But Diligence said, “No! No!
Those Apps should not be
on our system! They must go!
“They should not be installed
When our boss is not here!
Uninstall! Uninstall!
Said Diligence, wrought with fear.

“Have no fear, Diligence,”
Said the Vendor in Black.
“These apps are good apps.”
And he gave them a nod.
“They are great. Oh, so great!
They were built to work well.
They will save you more money
and make you feel swell.”

“Now, here is a new trick that I like.”
Said the vendor.
“They augment your data,”
Said the Vendor in Black.

“No! Not in our system!”
Said Diligence, quite hot.
“They should not change the data
in our system! They should not.
Oh, the errors they’ll make.
The mistakes I will find.
Oh, I do not like it!
Rewind, Rewind!”

Then Sally and I
Saw them merge our transactions.
We saw those two Apps
Put our systems in traction.
Bump! Thump! Thump! Bump!
For hours on end there was no reaction.

App One and App Two!
Power Down! Power Up!
Our processors maxed!
It was not abrupt!
In want of more memory,
swap space was used.
And our brand new SAN,
those Apps did abuse.

Then those Apps they spit out
A slew of reports.
Across all our data,
they said we were short.
And I said
“I do NOT like the way that they run.
If our boss saw this,
would he have bought one?”

Then Diligence said, “Look! Look!”
And trembled with fear.
“Our boss is on her way back!
Do you hear?
Oh, what will she do to us?
What will she say?
Oh, she will not like it
To find our systems this way!”

“So, DO something! Fast!” said Diligence.
“Do you hear!
I saw her! Our boss!
Our boss is near!
So, as fast as you can,
Think of something to do!
You must get results from
App One and App Two!”

So, as fast as I could,
I loaded Excel.
And I said, “With Excel
I can get meaning I bet.
I bet, with Excel,
I can use those reports yet!
Cut and Paste, Slice and Dice
Make our new reports useful and nice!”

“You see!” said the vendor
“Our new apps work great.
You’ll save.
Yes you’ll save.
Oh you’ll save
Ain’t that great!”

Then he left us the box
with the CDs inside.
And the Vendor went away
gleaming with pride.

“That is good” said Diligence.
“Vendor’s gone away. Yes.
But our boss will come back
She will find this big mess!
And the mess is so big
And through all systems spread,
We can not clean it up.
We are so dead!”

And THEN!
Who was back in the office?
Why, the Vendor!
“Have no fear of the mess,”
Said the Vendor in Black.
“I solve all your problems,
And so …
I have here another module
to answer your woes!”

Then we saw Vendor install
App Three, Your Original View.
For another small fee
our data renewed.
Our original views,
and our new views too
plus a hundred reports
and a slew of canned graphs
in bright shiny colors
to show us our gaffs.

Then Vendor was gone
with a tip of his hat.

Then our bass walked in
And asked of us two
“Did you accomplish your goals?
Tell me. How did you do?”

And Sally and I did not know
What to say.
Should we tell her
The things that went on here that day?

Should we tell her about it?
Or hope she never finds out?
Well …
What would YOU do
If your boss asked YOU?

This entry was originally posted on February 17, 2007.  It is being reposted not only because the spend analysis vendors were making a lot of noise last quarter, but because the spend analysis consultants are finding their workload at an all-time high — which means that many companies are waking up to the fact that there are only a handful of technologies, like spend analysis and optimization, that can save them money in this agflation-recession environment.  However, it has to be true spend analysis and not 100-reports-in-a-box.  In other words, when selecting your vendor, due to the large number of spend analysis solutions on the market that are not, at least in the doctor‘s view, true spend analysis solutions, it’s buyer-beware.  

Sourcing Innovation Welcomes Lexington Analytics as a Lead Sponsor

Sourcing Innovation is pleased to welcome Lexington Analytics as a lead sponsor. Lexington Analytics is a very appropriate sponsor for Sourcing Innovation because it believes in pushing the innovation envelope by using advanced data analysis techniques to find hidden savings opportunities in PxQ (price X quantity) data. Lexington Analytics was founded by Bernard Gunther, who has in the past been kind enough to post How much do you know about your spending? and Do you have a plan? right here on Sourcing Innovation. Bernie was one of the co-founders of The Buying Triangle, and has a long pedigree as a partner in several leading sourcing consulting firms.

Over the last few years, The Buying Triangle surprised skeptics by performing project after project for Fortune 500 companies that not only identified millions in savings opportunities, but also recovered millions of dollars in overspending and overcharges. Lexington Analytics has taken this key IP forward, continuing to refine those techniques to become one of the few consultancies to aggressively apply market-leading spend analysis technology and business intelligence techniques to commodity-specific procurement. LA typically builds not only an A/P view of spend, but also dozens of commodity-specific cubes to drill down on concrete savings and refund opportunities. Bernie and his Lexington Analytics team bring decades of data analysis expertise to each and every project.

The Lexington Analytics solution is based on the traditional prepare-analyze two-step, but with a crucial difference: with LA, it’s a continuous feedback cycle, as they employ state-of-the-art analysis tools (including BIQ) that allow them to rapidly create, analyze, and throw away data cubes until they identify a high value savings strategy. They don’t just create one cube, run a standard set of reports, and give you a “top ten spend” report. They create multiple cubes, run some analytics, look for anomalies, then drill in, out, and, if necessary, drill sideways until they’ve uncovered the hidden opportunities that canned analysis reports completely miss — opportunities that can often translate into massive additional savings.

For example, Lexington Analytics personnel helped a regional bank with $770 Million in spend develop a plan for saving $85 million. Using that plan, the bank was able to deliver $93 million in savings over the next 18 months. LA helped a financial services provider discover that total enterprise spending with a certain vendor with whom they had a $1.5 million contract, and who was classified differently in different systems by different departments, was actually billing $14 million, translating to substantially better discount levels. A national insurance company had established a corporate purchasing program with an office supply vendor, but employees were also using their corporate cards to purchase from the vendor’s retail outlets. This represented 20% extra cost for 3% of their total spend. Using the information provided by LA personnel, the vendor was able to return 0.6% savings to the company without making any changes to behavior or programs. And that’s just a few of LA’a success stories. They have many more (which they’d be more than willing to share if you contact them).

Please join me in issuing a sincere welcome to Lexington Analytics. If you are in the market for assistance in starting a spend analysis program, performing an opportunity assessment, improving your current spend analysis program with invoice-level analysis, or simply need some training or a jump-start to help your staff take your current program to the next level, I would recommend that you add LA to your list of potential partners. I’d also recommend that you take a few minutes to visit their site (through a Sourcing Innovation link) to let them know that you approve of their decision to support Sourcing Innovation – your #1 independent source for education and innovation in sourcing, procurement, and supply management.