Category Archives: rants

Why You Should NOT Build Your Own e-Procurement Platform

A couple of months ago, SI ran a short series on Why You Should Not Build Your Own e-Sourcing System, which also included pieces on Why You Should Not Build Your Own Spend Analysis, Why You Should Not Build Your Own e-Negotiation Platform, and
Why You Should Not Build Your Own Decision Optimization because he heard that a few public sector organizations have this crazy idea that they can build their own and that it can, somehow, compete with best-of-breed solutions on the market today. As per that series, this is not the case.

Neither is it the case that an organization should build its own C(L)M system, as per SI’s post last week on Why You Should Not Build Your Own Contract Management System. It seems that there are (at least) a few organizations that not only think they can (which is often true) but think they should (which is usually not a good idea). Unfortunately, it doesn’t stop there.

Since basic e-Negotiation and e-Procurement is a commodity, and there are even free and open source solutions for both still available on the net (like WhyAbe and archived versions of open source by Coupa and Bupros), some organizations and public sectors think they can roll their own and, believe it or not, do it cheaper and better than just acquiring a low-cost on-demand solution (which might even cost less than the resources the organization / public sector body would require to maintain their own software and hardware, not counting the dollars they would have to invest up front to roll their own). When it comes to B2B or B2C, building your own in this day and age is, well, ridiculous. With so many options to choose from, the chances of your organization not being able to find a cheap, easy solution that meets at least 80% of your needs, and 90% with a few minor process changes, is low. Not only are there no cost savings (which becomes clear when a full total cost of ownership is done, see this classic SI post on X), there’s no value generated by building your own solution. Inflation is coming back with a vengeance, GDP is slowed to a crawl in first world countries, and risks are multiplying faster than Fibonacci’s rabbits. Wasting money on anything with no risk of value generation is just not something 99.99% of companies can afford to do.

While most P2P functionality is straight forward, and the cycle, which has more steps than pre-contract Sourcing, is simpler as it is more tactical in nature, a few requirements, while simple in theory, are actually quite complex to implement technically. In particular, the following three functions are quite demanding to implement technically.

Requisition Management

While the process of managing an approved requisition is no more complicated than managing any other e-Document, the process of approving a requisition can be quite complicated as it could require one or more approvers in one or more departments with the rules for determining who approves dependent upon the item, it’s category, it’s dollar value, it’s (un)approved status, the overall amount of the requisition, and whether or not any affected budget for the buyer, category, or department would be exceeded if the requisition was approved. The approval chain could actually consist of multiple approval chains that need to be executed in parallel, which can possibly be overruled by the last approver in the sub-chain or the entire chain (if it had to get final approval from a VP or CXO because of the amount), and which might need to be approved all-or-nothing for the requisition to help the requisitioner. This implies the need for powerful, configurable, and flexible workflow management that is rather time-consuming and sometimes tricky to implement and not always going to be available in an open source solution that you can easily integrate into a roll-your-own solution.

Purchase Order, Invoice, & Good Receipt Management

Not only do all of the these e-Documents have to be tracked, but they have to be cross-correlated in many-to-many-to-many relationships. For example, a purchase order may need to be split across multiple vendors, each of whom may ship the order in pieces due to geographic stock location and customer locations, and issue multiple invoices, and then the shipments might arrive in pieces, requiring each invoice to be associated with multiple good receipts, or which might arrive in unison, require one goods receipt to be associated with multiple invoices. Similarly, a shipment might arrive before an invoice, requiring goods receipts to be associated with one or more purchase orders. There’s a lot of cross-correlation logic here. Plus, documents can come in as XML, EDI, CSV, PDF (which need to be processed using OCR), or platform specific formats – so there is a lot of pre-processing that needs to be done as well. And then an m-way match has to occur against each line, because, otherwise, the platform is not very useful.

e-Payments & Tax Reclamation

These days, an organization that wants to go e-Payment has to support ACH and wires, and do very difficult secure integrations into a bank; Paypal, Stripe, and similar online platforms for small businesses; and credit cards so its employees can use their P-cards, and integrate into a credit card processor. It’s a lot of integration work that has to be done precisely, because if anything is not done up to Bank, Paypal, or CC Processor spec, and it gets hacked, it will be on the hook for all of the fraudulent payments that will result. And that can add up to hundreds or thousands or millions of dollars very quickly. Very, very quickly. This is one example of just because you can, it does not mean you should.

You’re not buying running shoes here. Just don’t do it.

Procurement 2020, Are we on Track?

Long time readers, including those who worked through last year’s mega series on The Future of Procurement and The “Future” Trend Expose already know the answer to this, but with only 5 years left to go, it’s worth exploring this topic that was all the rage 5 years ago but now no longer a whisper, even from the voices that were once the loudest in their great proclamations.

Why the silence? Because, to be frank, we’re not even close to their predictions, predictions which, to be honest, should have already been met by now.

While there is a lot of cannon fodder to go back to, let’s take Sourcing Innovation’s post from four summers past, which was penned at the height of the 2020 blathering, and which took us back to a report released by Hackett in 2008! In the first of the grand prophecies, which laid out the hierarchy of supply, rather than make grand projections, Hackett simply laid out a set of seven core competencies that businesses would need to acquire. And even though leading providers have offered next generation solutions for each of these since the end of the last decade, progress along these paths is still few and far between.

Business Process Sourcing

Many companies are still taking a scattered approach to process sourcing and outsourcing and indirect spend in general. Some are using BPOs, some are using GPOs, some are using both, and some are simply hiring contingent labour to handle the processes the business does not want to do, or does not have the skills to do, in house.

Supply Performance Management & Supplier Management

Formal Supplier Management is still weak, or non-existent at many companies, and fewer companies still have, or use, modern platforms to manage the performance of their supply base, even though there are a number of second generation platforms out there that have quite extensive capabilities. (The capabilities that are out there will be described in detail in the next platform-based Spend Matters Pro series on Supplier Relationship Management, starting after the CLM series concludes, which will be co-authored by the doctor, the maverick, the prophet, and the anarchist!)

Knowledge Management

According to Hackett, Sourcing will need to master content-driven analytics which integrate external data into internal data models …. We’re not there yet. Less than 1 in 2 Procurement departments are even doing basic spend analysis, yet alone more advanced content-driven analytics using multiple internal and external data sources! Knowledge is still quite poor. (Maybe that’s because only the leading sorcerors in the leading Procurement departments read Sourcing Innovation and Spend Matters CPO?)

Talent Management

After years of reducing the training budget to almost zero following the last big recession in the late 2000’s, there’s still been no sign of restoration and talent is still not getting the training they need to do the best job they could do. Until this happens, there’s no way that Supply Management will be the career path of choice for new talent.

Next Level Strategic Sourcing

Most companies still aren’t doing true TCO modelling or using strategic sourcing decision optimization, which is the only other supply management technology (in addition to true spend analysis) that has been demonstrated to find year-over-year savings. And a true next level company should be at TVM modelling and decision optimization, multi-tier analysis, trending and predictive analytics, long-term strategic supply chain redesign, and other advanced initiatives that will save money now and for years to come.

New Product Development & Introduction

As Hackett said long ago, Supply Management will have to include advanced design-for-supply support that incorporates multi-tier cost modelling, scenario planning and optimization, but seeing as how the majority of Supply Management departments are still struggling with TCO and weighted RFXs and e-Auctions, even though companies like Arena Solutions and DirectWorks (formerly Co-exprise) have been promoting this for close to a decade, this is still a ways off from being main-stream.

In other words, even though 2020 is approaching fast, we’re still a long way from 2020 Vision in Supply Management, despite the doctor‘s best efforts.

What the Hell is Automated Spend Analysis?

While reading a “must-read” post on “next generation spend analysis” (which shall not be named or linked to because it was not must read and contained no useful information on spend analysis, and definitely did not contain anything that would make it next generation), the doctor encountered the claim that automated spend analytics yields spend intelligence. Now, despite claims to the contrary, there aren’t that many technologies in the Supply Management world that truly deliver spend intelligence (and that’s probably why there are only two advanced sourcing technologies that have been found to deliver year-over-year returns above 10%, namely decision optimization and spend analysis). Moreover, nothing about these technologies is automated — they require a skilled user to define the models, do the analysis, and extract the insights.

So if someone is claiming a technology offers spend intelligence, that perks up the doctor‘s ears. And if someone is claiming it offers spend intelligence and is automated, that really gets his attention because if it’s real, it deserves to be shouted from the rooftops, and, if it’s not, shenanigans must be called on the charlatans. And even though calling shenanigans on the charlatans won’t stop them, as proven by the fact that repeated exposes have been done over the years on mediums (who claim to talk to the dead, but really don’t) and televangelists (who claim God is telling them to raise money for personal jets even though they aren’t even religious, and if you don’t believe the doctor, then please feel free to donate to Our Lady of Perpetual Exemption), at least the truth will be out there for those willing to look for it.

the doctor knows what automated spend reporting is, what automated spend refresh is, what automated spend cleansing and enhancement is, and what automated spend insights are, but what the hell is automated spend analytics? And how does it provide spend intelligence?

So, the doctor did some research. According to a meritalk blog post, which defines it as a must for every Federal agency and which appears to be using Spikes Cavell’s spend analysis technology, it is the automated data collection, cleansing, classification, enrichment, redaction, collation, and reporting through cloud based systems, which makes sense, but this isn’t spend intelligence. This process will turn data into a collection of facts that provide the analyst with knowledge, and maybe even actionable insight, but not without human intervention.

A human will have to look at the reports and identify which opportunities are real and which are not. Simply knowing how much is spent by Engineering, spent on cogs, spent with Cotswell’s Cosmic Cogs, and shipped by Planet Express is not providing an analyst with any real intelligence. Knowledge on its own is not intelligence. Knowing that the average price paid per cog was $1.50 when the market price for the same cog appears to be $1.30 is not intelligence. Intelligence is know that the price of steel is projected to continue to drop due to an influx of new supply and a fall in current construction projects, that in a month the price is expected to be $1.20, that the best time to lock in a long term contract will be in six to eight weeks just before the steel price hits the expected low point, and how to go about sourcing that contract to get a long term price at or below $1.20.

Rosslyn Analytics, who claimed to launch the “world’s first, and fastest, fully automated cloud-based spend data integration service”, defines it’s platform as a web-based automated spend analytics platform, defines spend intelligence as an 8-step process that starts with planning and includes a detailed data analysis phase, both of which require human intelligence to complete.

Further searching turns up a post titled “can we ever fully automate spend analysis or do we need” on Capgemini’s Procurement Transformation Blog from 2013 that clearly states that on their own, the analytics tools cannot interpret the data so the tools must be programmed and algorithms developed which “tell” the software how the data should be mapped and that even though we have now reached a level where human interaction with a data analysis tool is diminishing … human intervention is still required to tell software what can be learned.

These are just three examples where bloggers, consultants, and solution providers all agree that while much of the spend analysis process can be automated, human intervention is still required to extract intelligence out of the facts that the tool identifies.

There is no automated spend intelligence, and any claims to the contrary are false. the doctor sincerely hopes that this is the last time he sees this phrase, because if he ever sees it again, a rant of epic proportions is sure to follow (and fingers will be pointed)!

Screwing up the Screw-Ups in BI (Repost)

Back in January of 2008, SI ran this now classic post by Eric Strovink, formerly of Opera Solutions, BIQ (acquired by Opera Solutions), and Zeborg (acquired by Emptoris, which was acquired by IBM). While writing tomorrow’s rant, the doctor was reminded of this classic post and how most companies and people screw up the basics of BI and spend analysis. Since this will put you in the right frame of mind to understand tomorrow’s post, the doctor has decided to repost it.

Baseline recently put a slide show on their site illustrating “5 Ways Companies Screw Up Business Intelligence — And How To Avoid The Same Mistakes,” with data drawn from CIO Insight. The slides are an excellent example of how mainstream IT thinking misses the essential problems of business data analysis.

Let’s take the “screw-ups” one at a time:

Spreadsheet proliferation (97% of IT leaders say spreadsheets are still their most widely used BI tool.)
Spreadsheets are one of the most valuable business modeling tools available, and IT might as well understand that they’re not going away. The problem is when spreadsheets (and offline tools like Access) are used inappropriately, to manipulate transactional data rather than drawing it in the right format from a flexible store. The solution provided by Baseline is to “cleanse and validate your data, then migrate the information to a central server/database that can be the backbone of any BI strategy.” Bzzt! Sorry, a central database won’t solve the analysis problem, and at the end of the day you’ll have just as many spreadsheets as before. That’s because a fixed schema data warehouse is a lousy analysis tool, and might as well be on planet Neptune as far as usability for the business analyst is concerned. There’s nothing wrong with a reference dataset, but business analysts need to be able to manipulate its structure as easily as a spreadsheet, or they will simply extract the raw data from it and manipulate the data offline, with the same slow, expensive, and uncertain results as today.
Systems can’t talk to each other (64% of IT leaders say integration and interoperability of BI software with other key systems such as CRM and ERP pose a problem for their companies.)
Right! Except that the Holy Grail of trying to extend a “centralized” database umbrella over completely disparate systems is both incredibly expensive and nearly impossible. Baseline suggests “[partnering] with a reputable systems integrator.” Good for them — at least they dodge this bullet rather than getting the answer completely wrong. The right answer is that business analysts should be able to construct BI datasets on their own, as needed, from whatever data sources are useful/appropriate, and it shouldn’t be difficult for them to do so. Concentrating all of the information under one umbrella isn’t necessary; many umbrellas can do the job, and if they’re easy to deploy, they’re both inexpensive and provide a better and more flexible answer.
No centralized BI program (61% say they don’t have a center of excellence of the equivalent of BI.)
And they’d be well advised to tread carefully, because BI systems have a track record of poor performance and poor customer satisfaction. Why? Because the analyses you can do with a fixed data warehouse are limited to the views set up a priori by IT or by the vendor, and those views are largely immutable. Baseline dodges this one, too, suggesting the “[creation of] a data governance and data stewardship program.” Can’t argue with that in principle, but a governance and stewardship program doesn’t actually put any meat on the table. How about putting tools into analysts’ hands that they can actually use? Right now?
Data lacks integrity (57% say poor data quality significantly diminishes the value of their BI initiatives.)
Hmmm, I wonder why the data are of such poor quality. Could it be that the BI system doesn’t really provide much insight? Could it be that the fixed schemas set up by IT or by the vendor don’t have any applicability to day-to-day questions? Could it be that the inability of the BI system to re-organize and map data on the fly causes errors to persist over time? Baseline recommends spending more money on data cleansing, which might make a cleansing vendor quite wealthy, but won’t help much. It typically isn’t cleansing that’s the problem, it’s (1) the fixed organization of the data, which is guaranteed to be inappropriate for any analysis that hasn’t been anticipated a priori, (2) the ad hoc reporting on it, which has to be easy to accomplish, as opposed to requiring IT resources (see below), and (3) the fact that cleansing can’t be accomplished on-the-fly (as it should be) by the business analysts themselves.
Managers don’t know what to do with results (58% say most users misunderstand or ignore data produced by BI tools because they don’t know how to analyze it.)
Even when BI is in place, nobody knows what to do with it. Baseline recommends that “IT staffers… should work closely and regularly with business managers to ensure that measurement, reporting, and analysis tools are supporting business goals.” But this is precisely the problem. For business analysts, BI systems are difficult to use and set up, it is difficult to create ad hoc reports, and it is impossible to change the dataset organization. It is also politically impossible to change the dataset organization if it is being shared by hundreds or thousands of users. How are you going to get them into the same room to agree on the changes?

So, Baseline is proposing (in essence) that IT resources sit cheek-by-jowl with business users, to ensure that they can get value out of a system that they otherwise could not use. This is certainly a “solution” of sorts, but it’s not practical. Either business analysts can use the system on their own, or the system will be of marginal value to them. It’s that simple.

101 Procurement Damnations – We’re Almost Halfway There

Our last post chronicled our 50^th Procurement Damnation that you, as a Procurement professional, have to deal with on a regular, if not daily, basis. If only these were the only 50 damnations clouding your mind and getting in your way. There are still 50 more damnations that are just as pervasive that seemingly exist only to pester you on a daily basis that we have not yet discussed!

However, before we get to the next 50, we thought it would be a good idea to summarize the list to date so that you could go back and review any posts in the series that you might have missed as this is SI’s biggest and most aggressive series to date, longer than both the 15-part “Future” of Procurement series and the 33-part “Future” Trends Expose series (that followed) combined and double the length of the maverick‘s 50 Shades of Pay series (assuming it gets completed) which, to date, only has 10 parts up and available for your reading pleasure.

There’s more that could be said, but much has been said in the 50 posts published to date and much more will be said in the next 50 posts, so, without further ado, here’s the first 50 for your reviewing pleasure.

Introductory Posts

Economic Damnations

Infrastructure Damnations