Author Archives: thedoctor

Why You Should Not Build Your Own e-Sourcing System, Part II Spend Analysis

In Part I, where we noted that Mr. Smith was right in his recent post on “thinking of building your own esourcing system please don’t” over on Spend Matters UK where he pleaded with those organizations, and particularly those organizations in the public sector, who thought they could build their own e-Sourcing system not to, we gave a host of reasons why only those organizations with the core business of software development and delivery specializing in Sourcing or Source-to-Pay should even consider the possibility. We also agreed with Mr. Smith that any other organization that even considered the possibility was

  • going to waste OUR money building it,
  • waste exorbitant amounts of money keeping the system up to date and compliant with ever-shifting legislation, and
  • only feed those dangerous delusions at best (and possibly create an epic disaster worse than the Smug cloud that ruined South Park because, of the 11 greatest supply chain disasters of all time, 8 were caused by technology failures and 6 by software platform failures!)

But we know this isn’t enough to convince the smuggest and most deluded from considering the notion. So we’re going to dive in and address some of the difficulties that will have be conquered, one primary module at a time, starting with spend analysis.

Even though every vendor and their dog thinks they can deliver a spend analysis system these days, the reality is that most vendors, including those with a lot of database and reporting experience, can’t. If vendors with significant experience in data(base) management and reporting can’t build a decent spend analysis system, what makes you think your organization can?

A spend analysis solution must be:

  • Powerful
    and support multiple spend analysis cubes, with derived and range dimensions, stored in public and private work spaces;
  • Flexible
    and support multiple categorization schemes, vendor and offering families, and user defined filters and drill downs;
  • Manageable
    with user defined data mappings and cleansing rules, hierarchical rule priorities, and easy enrichment;
  • Open
    and easy to get data in, out, and mapped; and
  • Informative
    with built-in report libraries, a powerful report builder, and an intuitive report customization feature.

This is not easy. Let’s start with flexibility. Most vendors probably have their goods and services mapped against UNSPSC, which your buyers of domestic goods are familiar with, but globally traded goods are probably mapped against HTS, which your tax division wants, your organization probably has its own GL codings that are required to keep Accounts Payable happy, and none of these categorization schemas are suitable for real spend analysis. As a result, you probably need to maintain at least four separate categorization schemas (for buyers, traders, accounts payable, and real analysts). If you think you can easily achieve this by slapping a report builder on top of an open source relational database, think again.

Let’s move on to power. One cube is never enough. If you’re an organization of reasonable size, doing year over year spend analysis over a reasonable time frame, you’re looking at millions, if not tens of millions of transactions. If you believe that you can dump all of that in one cube, and make sense of it, assuming you can design a system that can even build that cube without crashing (it’s big data, remember), you’re probably living in ImaginationLand (which is a very dangerous place to be).

We cannot forget about openness. The data you need will not live in the Spend Analysis system. It will live in the ERP (Enterprise Resource Planning). It will live in the Accounts Payable System. It will live in the TMS (Transportation Management System). It will live in the WIMS (Warehouse Inventory Management System). It will live in the VMS (Vendor Management System). And so on. Every one of these systems will have a different schema, it’s own data master, and, probably, duplicate vendor and product entries with various spellings of the name, locations, and so on.

Nor can we forget about manageability. It must be easy to map, normalize, clean, and map all of the data that is pushed into the system — by hand. AI doesn’t work. Every organization uses its own classification and shorthand, every department uses its own variations on the theme, and no system can figure out every error a human can make. All AI systems do is pile on rules until there are more collisions than correct exception mappings. That’s why a spend analysis system not only has to support multi-level rules, but help the user define appropriate multi-level rules and understand, when a transaction is mis-mapped, which rule did the mapping, what exception rule is required, and how broad that rule should be.

This leaves us with the need to extract useful information that can be used to identify real saving or value generation opportunities. No canned set of reports can do this. Standard reports can indicate where we can begin to look, but simply knowing a spend is high, or higher than market average, does not indicate why (locked in prices, bundled in services, quality guarantees, maverick spend, supplier overcharges) or what factors, if addressed would decrease spend.

And while this is just a high level overview of the challenges, the hope is that it is sufficient enough to convince you that development is not an easy task and not something that the average organization should remotely entertain.

Why You Should Not Build Your Own e-Sourcing System, Part I

In a recent post titled “thinking of building your own e-sourcing system please don’t” over on Spend Matters UK, Mr. Smith (who went to Washington, as per Buy, Buy, Buy, Once Bitten Twice Shy) asks you to please, please, please not build your own e-Sourcing system because, apparently, a few public sector organizations have this crazy idea that they can build their own and that it can compete with best-of-breed solutions on the market today.

Wow! Today’s best of breed systems have been built on fifteen-plus (15+) internet years of development, implementation, integration, and customer support experience by seasoned professionals who have had numerous bouts with weariness and wisdom. (And since we all know that internet years are measured in cat years, that’s really ninety-plus years of experience.) How could any average organization, especially in the public sector which is typically behind in technology and running on the B-Team (since unionized pay scales typically mean that they can’t afford the A-Team that commands private sector pay scales) really think they can come up with anything close?

In addition to Mr. Smith’s arguments that, especially in the public sector, you are:

  • going to waste OUR money building it,
  • waste exorbitant amounts of money keeping the system up to date and compliant with ever-shifting legislation, and
  • only feed those dangerous delusions (until the Smug reaches critical mass and puts us at risk of a disaster of epic proportions),

there are dozens of reasons NOT to build your own e-Sourcing system, or to even think that there is the slightest of chance you could build your own.

In addition to the standard reasons of:

  • Lack of Sourcing Domain Experience
  • Lack of Software Design Skills
  • Lack of A-Team Software Development Talent

in Sourcing, you also have to deal with the traditional software challenges of:

  • Big Data
  • Real-Time Requirements in a Distributed System
  • Variable Workflows

as well as a host of challenges in each of the main, traditional, areas of:

  • Spend Analysis
  • e-Negotiation (RFX & e-Auction)
  • Decision Optimization

which, to make it abundantly clear that no public and private organization should even remotely consider building their own e-Sourcing system, will be discussed in detail in the next three posts. Unless your core business is a software development and delivery organization specializing in Sourcing or Source-to-Pay, when it comes to building a modern e-Sourcing system to meet the needs of the organization and identify savings and value, just don’t do it. Put those Nike’s back in the closet and break out those Carolinas.

Spend Analysis Solution Selection: What to Look for in Software and Services

As the author penned in Spend Visibility: An Implementation Guide,

“Almost any attempt by an organization to analyze spending patterns is likely to be fruitful, especially if there hasn’t been a serious prior attempt. It is easy to find thousands of breathless testimonials about a particular product or method — independent of the quality of the product or method — because almost any product or method will find savings if a spend visibility initiative has never been launched before. In the land of the blind, the one-eyed man is king“.

This simple fact has confused end-user organizations and analysts for many years. In fact, it has convinced most spend visibility vendors (and most analysts) that spend visibility is a fundamentally simple process of mapping Accounts Payable spend, and then drilling for dollars.

But Nothing Could Be Further From The Truth!

What is not so obvious is that this initial burst of savings is short-lived; and that many of the “quick saves” that result are unsustainable.

Especially if an organization does not select the right solution in the beginning that will allow it to define, and implement, a strategy that will allow it to identify continued savings year-over-year after the initial burst of savings are captured.

However, there’s no reason for an organization not to select the right software or services, because, it’s easy to select the right solution once you are informed. If you don’t know where to start, the next Next Level Purchasing Association (NLPA) members only webinar on July 28, 2015 @ 8:30 am PDT, 11:30 am EDT, and 16:30 pm BST, will provide you with a starting point as you evaluate software and services providers.

Specifically, this webinar will focus on helping an organization identify:

  1. key features of a spend analysis platform,
  2. critical requirements for successful services, and
  3. what to look for in a full-service solution

so that the organization may achieve spend analysis success. In particular, the kind of success that will generate a year-over-year average savings of 10%+.

Space is limited, and only NLPA members will have the opportunity to attend this webinar hosted by the doctor of Sourcing Innovation, but Basic Membership is Free, so there’s no reason to miss out. Sign up today, and very shortly you’ll receive the notice of the upcoming webinar that will allow you to register for this very informative webinar.

Two Hundred and Sixty Five Years Ago Today

Only one year and 20 days after its establishment as a town, the City of Halifax was almost completely destroyed by a fire 265 years ago today. Everyone remembers the great Halifax Explosion of 1917 when the SS Mont-Blanc, a French cargo ship loaded with explosives, collided with the SS Imo, a Norwegian vessel, caught fire, and burst in a cataclysmic explosion that devastated the Richmond District, killed 2,000, and injured another 9,000. But this wasn’t the first time Halifax was nearly destroyed by fire.

The first time was on July 11, 1750 when Halifax recorded the first fire of major proportion in Canada which almost wiped out the entire town. [Sources: Halifax.ca, FireHouse(.com) and Wikipedia] That’s probably why published fire regulations in Halifax date back to September 29, 1752 and
the Halifax Regional Fire and Emergency Service dates all the way back to 1754 and why Nova Scotia lays claim to a host of first in Canadian firefighting, including:

  • the first hand-propelled fire engine
  • the first steam-propelled fire engine
  • the first motorized pumper

And Halifax came close to being destroyed again in 1786 when a great fire raged in the woods on the outskirt of the city, a fire so great that the town was so enveloped in smoke for many days, as almost to impede business. (Source: History of Halifax City)

In other words, despite the fact that fate apparently wants to burn Halifax to the ground, we Haligonians are tough stock.

Correlations are Good, Causations are Better, but Models are Best!

the maverick recently penned a great post on “Spurious Correlations, 150% Cost Savings and How to Justify Your Next Procurement Project” on Spend Matters that expounded upon the classic problem of second rate analysts, who didn’t read the classic post where the Brain gives Pinky a lesson in Statistics, using correlation to infer causation. If you listen to these analysts, you’ll find yourself in the same situation Roy Anderson was in when he was former MetLife CPO. Namely, the situation where if I added up all the promised savings from vendors and Aberdeen Reports, I’d be saving over 100% and suppliers would be paying me money! Not very likely, is it, but definitely the conclusion you’d draw if you stacked enough Aberdeen reports end to end!

After all, with enough data, you can find all sorts of near perfect correlations between (almost) completely unrelated data sets. For example, Pierre points out that if you go to tylervigen.com and check out the spurious correlations on the site, you’ll find out that there’s a near perfect correlation between

  • the number of people who drown after falling out of a fishing boat and the marriage rate in Kentucky (r=0.95),
  • the total number of computer science doctorates awarded in the US and the total revenue generated by arcades (r=0.99), and
  • the annual number of automotive suicides and the number of Japanese passenger cars sold in the US (r=0.94).

And while you might believe that computer science doctoral candidates spend all their free time in arcades, do you believe that buyers of Japanese passenger cars buy them to commit suicide or that somehow the marriage rate in Kentucky has something to do with the number of people who drown after falling out of a fishing boat? (I hope not!)

As Pierre notes, it’s important to have a good ROI model that really looks at the “R” and the “I” realistically. A model that uses ranges that allows you, as an analyst, to play around with assumptions and adjust the results based upon modifications to the assumptions. Procurement might want to be aggressive, but management might want to be conservative. Procurement might assume an abundance of supply, but Engineering, knowing that only a couple of suppliers are qualified to produce the refined raw materials needed, might want to assume a lack of supply based on the fact that these refined raw materials are becoming increasingly sought after. And so on.

Without a detailed model that captures all the cost components and the assumptions they are based on, Procurement can’t be realistic in its projections or its project requests. Analyst reports with benchmark data are a great starting point to identify where to look for savings, but the savings still have to be validated before a proposal is put forward.