Category Archives: Technology

Thirty Two Years Ago Today …

… Halley’s Comet Teaches Us a Thing or Two About Comets!

It was the last time Halley’s comet appeared in the inner solar system (where it won’t appear again for another forty-three years (in 2061). And it taught us a thing about comets. As per Wikipedia:

“During its 1986 apparition, Halley’s Comet became the first comet to be observed in detail by spacecraft, providing the first observational data on the structure of a comet nucleus and the mechanism of coma and tail formation.[15][16] These observations supported a number of longstanding hypotheses about comet construction, particularly Fred Whipple’s “dirty snowball” model, which correctly predicted that Halley would be composed of a mixture of volatile ices – such as water, carbon dioxide, and ammonia – and dust. The missions also provided data that substantially reformed and reconfigured these ideas; for instance, it is now understood that the surface of Halley is largely composed of dusty, non-volatile materials, and that only a small portion of it is icy.”

Why is this important? It’s not the only comet, and its not the only periodic comet. But considering this is likely the comet that showed us comets could break up, and throw off of asteroids, which many scientists believe was a primary cause of the extinction event that wiped out the dinosaurs, the insight it has provided us is scientifically vital. If an asteroid throw off of a comet was a major contributing factor in the dinosaur extinction, it’s something we don’t want to happen to us (provided we don’t climate change the planet to point its unliveable — after all, it’s already 2 minutes to midnight).

And why is this important to supply management? We rely on predictive algorithms every day, predictive algorithms which have their roots in interpolation algorithms developed by the early mathematical greats to, guess what, predict the periodic orbit of comets!

One Hundred and Thirty Five Years Ago Today …

The first standardized incandescent electric lighting system employing overhead wires, built by Thomas Edison, begins service in Roselle, New Jersey, just a year after Edison switched on the first steam-generating power station at the Holborn Viaduct in London, England.

In other words, while the vast majority of people alive today who were born in a first world country grew up with electric street lighting, it’s not that new. And when you consider the amount of time we’ve been on this planet from a scientific evidence point of view, it’s amazing how far technology has progressed since the delivery of the first stable feeds a little over 135 years ago …

What’s the right level of safety stock?

Severe weather events and transportation disrupting natural disasters are on the rise, and the only thing that we can be sure of is they are going to keep coming fast and furious in the near future. We don’t know when, where, or what extent the impact will have, but we know it’s coming.

The resulting disruptions to your supply chain will last days, weeks, or months. And if the part of your supply chain that is disrupted is one supplying a critical component that is sole-sourced or in a supply shortage, any and all products it is used in will be in jeopardy once the inventory runs out. As a result, JiT inventory is becoming a thing of the past. However, too much inventory on hand is NOT a good thing. You want a balance between JiT and everything you need for the planned production run. And that balance could be anywhere from a few extra days (for inventory that can be obtained from another source on short notice) to a a few months (for something otherwise hard to get).

But how do you figure out the right stock levels? It’s not just rarity. After all, stock costs money and ties up working capital … capital that likely has better uses. After all, early supplier payments can bring cost reductions. Investments can bring recurring cast. R&D can develop new, more profitable, products for sale. And so on.

So how do you determine the right level of safety stock? Expand the working capital optimization model to allow for a variable disruption cost based upon variable stock levels, each of which has an associated investment cost (in the form of tied up working capital), and determine the stock levels from the investment that optimizes working capital.

Again, the right level of safety stock falls out of working capital optimization.

What Should Drive M&A?

Last year was obviously the beginnings of a new M&A frenzy cycle in the Procurement Vendor space. Big names were scooped up by bigger names in an effort to expand their reach and/or capability in an effort to become the biggest name of them all. But is this good for Procurement departments? It depends on the synergy inherent in the acquisition. As summarized in the doctor‘s guest post over on the Synertrade blog on “Surviving a M&A: The Customer Perspective”, M&A synergies come from operational synergies, customer synergies, or solution synergies.

And these synergies will either come from complementarity or redundancy. Both can, theoretically, have a big impact on the bottom line, but one impact will likely be viewed much more positively than another from the eyes of customers. While bankers and financiers might be satiated with redundancy synergies when overhead prices get slashed and immediate profits rise (thanks to SaaS deals that insure license revenue keeps coming in month after month in the near term), customers are not always happy when their support teams, with whom they have built a relationship with over months or years, are eliminated overnight in one fell swoop.

That’s why the doctor believes that complementarity should drive synergies. For the big wanting to get bigger, they should seek to acquire a smaller provider that provides them with the synergy of complementarity across the customer, solution and operations dimensions. Specifically:

  • Customerthe provider of interest should have a largely non-overlapping customer base that could make use of the company’s solution in unison with the smaller provider’s solution — for e.g., if a S2P company without in-house analytics is trying to acquire a BoB analytics firm, that firm could likely use part or all of the acquirer’s platform
  • Operationsthe unison of the providers should allow both parties to do more with the same back-office staff; i.e. the combined company should be able to grow without adding staff (and, moreover, the current staff should, more or less, be the best staff to grow the combined company)
  • Solutionthe solutions should complement nicely without too much work and should not overlap too much

Vendors should not pursue mergers that get synergy from redundancy. Having to scrap platforms, cut people, or, even worse, having to make decisions that negatively impact the current customer base (that talks to their peers).

It might be the case that the best provider is not as big as desired, or that the best provider doesn’t have all the desired solutions, but, as the tortoise taught us, slow and steady wins the race. And even if the new combined company has to build a bit more than they would like to, a combined, synergistic, team always has an edge.

Why Do We Still have First Generation ERP/Data Warehouse BI?

the doctor was recently asked by a senior consultant if a CFO was right when he said why should I use Spend Analysis if my ERP has BI functionality that allows me to do ‘any’ analytics and generate reports … and I only have one ERP instance as the company was relatively small (< 100M).

How is the CFO wrong? Can we even count the ways? First of all, let’s go back ten (long years) to when SI published this great post from the spend master himself, Eric Strovink on screwing up the screw-ups in BI where he noted that Baseline, in their efforts to defend AI, were simply pointing out more holes in the process. In this post, the spend master noted:

1. 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 … which, as every CFO and CIO knows, is way too many.

2. 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 … but most BI tools only make it easy to construct datasets and reports on data in the ERP. And you NEVER, EVER, EVER have all the data you need in the ERP. Some is in the AP. Some is in the sourcing and procurement systems. Some is in the WIMS. And then there are market data feeds that can provide insight, not in the ERP.

3. While BI is said to be the cornerstone of a governance program, a governance and stewardship program doesn’t actually put any meat on the table … whereas modern spend analysis systems do.

4. While BI can support data integrity, 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.

5. 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 … especially compared to spend analysis.

And this doesn’t even begin to address the facts that

6. BI reports are pretty generic, and not fine tuned to Sourcing, Procurement, or Finance. Modern SA systems, built by Sourcing, Procurement, and Finance professionals, have out of the box reporting fine-tuned to the needs of sourcing, procurement, and finance professionals that report on spend by category, supplier and metrics by category and supplier with easy drill down and segmentation by department, category, etc.

7. BI engines work on one schema — the ERP schema. And this is not always appropriate for Sourcing and Procurement who need to manage by category. and then do what if analysis against different re-categorizations to try and find the best way to source and procure for the organization. Modern SA tools allow for the creation of different schemas, different cubes on those schemas, and different views on those cubs. Power not in the BI.

8. BI engines expect the data in the ERP. SA systems don’t. They can import data from multiple systems, flat files, market feeds, etc. — put it in private, or public workspaces, reclassify and modify and augment the data as needed, and create true intelligence on a category or a supplier — not just a summary of last year’s spend by product or supplier.

9. The ability of first (and even second generation) BI engines to create arbitrary reports is considerably overstated. Most of them limit the facts and dimensions that can be used in reports to those in defined tables, and limit the self-service reporting to modification of pre-defined templates. Not the freeform capability of a modern Tableau or Qlik solution, and definitely not the freeform capability in a best in class Spend Analysis solution that can allow any dimensions or facts to be used and reports and dashboards to be created using any defined report components in an easy drag and drop manner.

And so on. Hopefully by now you get the point — especially when there are SA solutions out there that start at only a few thousand a month and provide at least 10 times the value of that outdated BI solution the ERP company should be paying you to use. (The technical debt they owe you on this is huge!)