Category Archives: Best Practices

Mayday! M’aidez!? the doctor hears your plea. Happy May Day!

Dear Sourcing / Procurement / Source-to-Pay+ Vendor,

Are you struggling to grow in the stagnant economy brought on by rising consumer debt, unemployment rates, elevated interest rates, and recessionary fears which is contributing to the ongoing reduction in overall spend on software and SaaS solutions, including yours (even though they are desperately needed by companies reliant on consumer spend to minimize their costs, optimize their buys, and survive until the next growth period in the oscillating economic boom-bust cycles brought on by allowing billionaires* to play with monetary markets with little regulation)? You’re not alone! Dozens of companies fail or voluntarily close their doors in our space every year and dozens more need to get acquired to survive.

While there is no guarantee of success (at least until you get funded by a large VC or PE with very deep pockets and the ability to insert you into their other businesses or get acquired by a company too big to go anywhere for two decades [i.e. a failure of that company would result in an acquisition because too many companies depended on them]), there are ways to greatly increase your odds. Especially since there are ways to guarantee failure in our space. (Remember, when you are delivering product, it has to do something. You can’t really be The Producers when you’re selling a product versus IP.)

So, what can you do to increase your chances?

1. Ensure you have a core team that covers all the bases.

Read a few good books on building a successful startup (which didn’t really exist 20 years ago, so while founders in the early 2000s in our space had an excuse for not knowing what to do, you don’t). Definitely include Garry Mansell’s Simplify to Succeed on your list as he goes great job of describing the core roles and skills the founding team must share between them.

2. Follow and Implement Best Practices

the doctor penned a series last year that chronicled 10 + 2 best practices that will help increase your chances for success. While the list is not exhaustive, it’s a great start. If every company did all of these, they’d at least be more prepared out of the gate for the harsh reality of a back-office SaaS startup.

3. Stop making the same mistakes that keep being made over and over and over again!

the doctor has been an analyst for eighteen (18) years and an independent consultant for over (20) years. As he noted in a previous post, during that time he’s reviewed/researched over 500 software/SaaS companies in Source-to-Pay+ in-depth, and (co-)written up over 350 of them here on Sourcing Innovation or on Spend Matters between 2016 and 2022.

(Let’s spell it out so it sinks in. FIVE HUNDRED PLUS software/SaaS vendors reviewed/researched and THREE HUNDRED AND FIFTY PLUS software/SaaS vendor solutions written up for public access! How many analysts still active in our space can make that claim?) (The answer, just a few. the doctor believes you can count them on one hand.)

As the doctor has reviewed, followed, done diligence, and/or worked with these companies, and seen them grow, get acquired, fail, or voluntarily shut their doors, he’s seen the best practices they adopted and the mistakes they make. And some of these mistakes he’s seen over and over and over again for the past two decades. And he’s tired of them, not just because there’s likely a dozen business books out there that will tell you not to do them (although they’ll probably spend a whole chapter you don’t have time to read to get to the point), but because they are preventing companies with good solutions and good intent from going anywhere.

So, in the hopes that he can prevent even a handful of companies from making these same old mistakes again (and limiting their chances of success), he’s going to cover fifteen (15) mistakes he sees over and over again in every generation of founders in the hope that the next generation of founders stops making them!

So be sure to follow Sourcing Innovation / the doctor closely this month!

* And if our governments won’t heavily regulate the ability of billionaires to manipulate markets or hire and fire tens of thousands of people at a time just to maintain unsustainable growth rates in large enterprises, maybe Robert Reich is right and they shouldn’t exist. After all, at the 100M mark you can literally own everything you could ever need and use for a lifetime as that’s enough for a personal plane and a personal yacht in addition to a couple of nice houses and a few nice cars …

You Don’t Need Bold Steps to Transform Procurement; Foundational Will Do Just Fine

But if you want to call the steps bold, go ahead, no one will challenge you because in many Procurement departments you have to be bold to force the first steps.

A recent article over on 3news.com did a great job of summarizing those procurement steps for a transformed procurement structure in 2024, proving that the state of affairs is the same globally and the good advice the same globally.

The article had five solid suggestions that are universally true globally across direct, indirect, services, and complex procurements. Since you can read about them in depth in the aforementioned article, as well as numerous posts here on Sourcing Innovation, we’ll just summarize them here.

Spend Analysis

If you don’t know what you’re spending where, with whom, and why, you won’t be able to improve it.

Category Managed Procurement

There’s no one size fits all procurement strategy and, for sourcing, procurement technology, so taking it on a category basis is a great start.

Cost Savings and Cost Avoidance

You can’t always find savings in an inflationary economy, so you have to increase focus on cost avoidance and ensure that nothing is bought that isn’t needed, and costs are maintained where they can’t be decreased.

Digitization / e-Procurement

Use digital systems to undertake e-Procurement, and, in particular, focus on ePro/I2P/P2P as you want the core Procurement process digitized, and POs and Invoices in particular, as you can’t analyze spend you can’t capture, and you can’t ensure you’re paying the right price without a system to enforce it, so if you don’t have a modern e-Procurement system, get one.

Sustainable Procurement

Do your best to procure responsibly to reduce waste, energy consumption, and overall costs.

About the only core requirements that are missing are:

RFX

Make sure you can get good, documented, quotes to back up your Procurements.

Supplier Management

Make sure you can identify, onboard, manage, and track all of your suppliers throughout the business relationship lifecycle.

 

It’s all Procurement 101, but if your organization hasn’t taken any of these steps, you may have to be bold and force your organization into the modern Procurement age.

Enterprises have a Data Problem. And they will until they accept they need to do E-MDM, and it will cost them!

insideBIGDATA recently published an article on The Impact of Data Analytics Integration Mismatch on Business Technology Advancements which did a rather good job on highlighting all of the problems with bad integrations (which happen every day [and just result in you contributing to the half a TRILLION dollars that will be wasted on SaaS Spend this year and the one TRILLION that will be wasted on IT Services]), and an okay job of advising you how to prevent them. But the problem is much larger than the article lets on, and we need to discuss that.

But first, let’s summarize the major impacts outlined in the article (which you should click to and read before continuing on in this article):

  • Higher Operational Expenses
  • Poor Business Outcomes
  • Delayed Decision Making
  • Competitive Disadvantages
  • Missed Business Opportunities

And then add the following critical impacts (which is not a complete list by any stretch of the imagination) when your supplier, product, and supply chain data isn’t up to snuff:

  • Fines for failing to comply with filings and appropriate trade restrictions
  • Product seizures when products violate certain regulations (like ROHS, WEEE, etc.)
  • Lost Funds and Liabilities when incomplete/compromised data results in payments to the wrong/fraudulent entities
  • Massive disruption risks when you don’t get notifications of major supply chain incidents when the right locations and suppliers are not being monitored (multiple tiers down in your supply chain)
  • Massive lawsuits when data isn’t properly encrypted and secured and personal data gets compromised in a cyberattack

You need good data. You need secure data. You need actionable data. And you won’t have any of that without the right integration.

The article says to ensure good integration you should:

  • mitigate low-quality data before integration (since cleansing and enrichment might not even be possible)
  • adopt uniformity and standardized data formats and structures across systems
  • phase out outdated technology

which is all fine and dandy, but misses the core of the problem:

Data is bad (often very, very bad), because the organizations don’t have an enterprise data management strategy. That’s the first step. Furthermore this E-MDM strategy needs to define:

  1. the master schema with all of the core data objects (records) that need to be shared organizational wide
  2. the common data format (for ids, names, keys, etc.) (that every system will need to map to)
  3. the master data encoding standard

With a properly defined schema, there is less of a need to adopt uniformity across data formats and structures across the enterprise systems (which will not always be possible if an organization needs to maintain outdated technology either because a former manager entered into a 10 year agreement just to be rid of the problem or it would be too expensive to migrate to another system at the present time) or to phase out outdated technology (which, if it’s the ERP or AP, will likely not be possible) since the organization just needs to ensure that all data exchanges are in the common data format and use the master data encoding standard.

Moreover, once you have the E-MDM strategy, it’s easy to flush out the HR-MDM, Supplier/SupplyChain-MDM, and Finance-MDM strategies and get them right.

As THE PROPHET has said, data will be your best friend in procurement and supply chain in 2024 if you give it a chance.

Or, you can cover your eyes and ears and sing the same old tune that you’ve been singing since your organization acquired its first computer and built it’s first “database”:

Well …
I have a little data
I store it on my drive
And when it’s old and flawed
The data I’ll archive

Oh, data, data, data
I store it on my drive
And when it’s old and flawed
The data I’ll archive

It has nonstandard fields
The records short and lank
When I try to read it
The blocks all come back blank

I have a little data
I store it on my drive
And when it’s old and flawed
The data I’ll archive

My data is so ancient
Drive sectors start to rot
I try to read my data
The effort comes to naught

Oh, data, data, data
I store it on my drive
And when it’s old and flawed
The data I’ll archive

Beware of Magical Thinking In Your Procurement!

Back in 2017 (yes, that was 7 years ago, but the subject is still relevant), the doctor penned a post asking if there was magical thinking in your procurement noting that:

the Procurement Department that is getting the worst deal is the one that hallucinates the most — and needs to — in order to keep their worldview intact

And, furthermore, it was these Procurement departments that were most against modernizing their processes or platforms because their worldview requires them to believe that the antiquated processes and (severely) outdated platforms they are (still) using are just fine. (And they don’t recognize that their Procurement departments still run on the island of misfit toys principle — staffed with people who are nearing retirement, related to the boss, or technologically adverse and have been doing it this way for far too long.)

the doctor also noted that the easiest way to identify these organizations was by their telltale arguments of:

  • our processes are just fine, we just need more people
  • our platform is just fine, we just need more people
  • it’s not worth the cost, and it will slow us down

which were soon augmented with the additional telltale arguments of:

  • the problem isn’t with us, it’s with logistics / risk management / compliance / support
  • the problem isn’t with us, it’s the suppliers who aren’t holding up their end of the contract
  • our needs are just too unique and there’s nothing out there that will close the gaps

as supply chains started to crumble under disruptions. Because, if you just gave them more time, money, and people, everything would work out fine with a little pixie dust.

But we know there’s no silver bullet, and the only answer is to implement the best technology, with the best processes, so you can identify the biggest risks, plan mitigations, detect when they have occurred, respond quickly, and, the rest of the time, deal with exceptions and not standard operating procedures that can be entirely automated.

And, in the late 2010s, that was the extent of the magical thinking theorem. But now, thanks to the Gen-AI garbage marketing overload, and the addition of tail end Millenials (who replaced those put out to the Procurement pasture when they called it quits during COVID or when companies tried to force their return to the office), we have a new corollary to the the Magical Thinking Theorem:

the Procurement department getting the worst deal is also the one that thinks they only way to solve their problem and get the best deal is to adopt and implement Gen-AI as fast as possible

because the Millenials, who grew up glued to their smartphones, and always received instant gratification via Google and Apple, believe there is an app-for-everything and that a natural language Gen-AI app combines the best of both worlds and will solve all their problems.

Their thinking is not only as magical as the last generation thinking (that more time, money, and people can solve anything), but more dangerous (because their answer is to just turn their problems over to the artificial idiocy machine and blindly accept whatever comes out of it, no matter how hallucinatory or ridiculous the answer is).

the doctor said it before and he’ll say it again. There’s no room for magical thinking in Procurement. Just like alchemy needed to be replaced with science, magical thinking needs to be replaced with realist thinking, and random unpredictable Gen-AI replaced with proven deterministic procedural (rules-based) solutions that use tried and true mathematical techniques. (Because, the classic analytics, optimization, and machine learning that you have been ignoring for two decades will do just fine.)

Spendata: The Power Tool for the Power Spend Analyst — Now Usable By Apprentices as Well!

We haven’t covered Spendata much on Sourcing Innovation (SI), as it was only founded in 2015 and the doctor did a deep dive review on Spend Matters in 2018 when it launched (Part I and Part II, ContentHub subscription required), as well as a brief update here on SI where we said Don’t Throw Away that Old Spend Cube, Spendata Will Recover It For You!. the doctor did pen a 2020 follow up on Spend Matters on how Spendata was Rewriting Spend Analysis from the Ground Up, and that was the last major coverage. And even though the media has been a bit quiet, Spendata has been diligently working as hard on platform improvement over the last four years as they were the first four years and just released Version 2.2 (with a few new enhancements in the queue that they will roll out later this year). (Unlike some players which like to tack on a whole new version number after each minor update, or mini-module inclusion, Spendata only does a major version update when they do considerable revamping and expansion, recognizing that the reality is that most vendors only rewrite their solution from the ground up to be better, faster, and more powerful once a decade, and every other release is just an iteration, and incremental improvement of, the last one.)

So what’s new in Spendata V 2.2? A fair amount, but before we get to that, let’s quickly catch you up (and refer you to the linked articles above for a deep dive).

Spendata was built upon a post-modern view of spend analysis where a practitioner should be able to take immediate action on any data she can get her hands on whenever she can get her hands on it and derive whatever insights she can get for process (or spend) improvement. You never have perfect data, and waiting until Duey, Clutterbuck, and Howell1 get all your records in order to even run your first report when you have a dozen different systems to integrate data from, multiple data formats to map, millions of records to classify, cleanse and enrich, and third party data feeds to integrate will take many months, if not a year, and during that year where you quest for the mythical perfect cube you will continue to lose 5% due to process waste, abuse, and fraud, and 3% to 15% (or more) across spend categories where you don’t have good management but could stem the flow simply by identifying them and putting in place a few simple rules or processes. And you can identify some of these opportunities simply by analyzing one system, one category, and one set of suppliers. And then moving on to the next one. And, in the process, Spendata automatically creates and maintains the underlying schema as you slowly build up the dimensions, the mapping, cleansing, and categorization rules, and the basic reports and metrics you need to monitor spend and processes. And maybe you can only do 60% to 80% piecemeal, but during that “piecemeal year”, you can identify over half of your process and cost savings opportunities and start saving now, versus waiting a year to even start the effort. When it comes to spend (related) data analysis, no adage is more true than “don’t put off until tomorrow what you can do today” with Spendata, because, and especially when you start, you don’t need complete or perfect data … you’d be amazed how much insight you can get with 90% in a system or category, and then if the data is inconclusive, keeping drilling and mapping until you get into the 95% to 98% accuracy range.

Spendata was also designed from the ground up to run locally and entirely in the browser, because no one wants to wait for an overburdened server across a slow internet connection, and do so in real time … and by that we mean do real analysis in real time. Spendata can process millions of records a minute in the browser, which allows for real time data loads, cube definitions, category re-mappings, dynamically derived dimensions, roll-ups, and drill downs in real-time on any well-defined data set of interest. (Since most analysis should be department level, category level, regional, etc., and over a relevant time span, that should not include every transaction for the last 10 years because beyond a few years, it’s only the quarter over quarter or year over year totals that become relevant, most relevant data sets for meaningful analysis even for large companies are under a few million transactions.) The goal was to overcome the limitations of the first two generations of spend analysis solutions where the user was limited to drilling around in, and deriving summaries of, fixed (R)OLAP cubes and instead allow a user to define the segmentations they wanted, the way they wanted, on existing or newly loaded (or enriched federated data) in real time. Analysis is NOT a fixed report, it is the ability to look at data in various ways until you uncover an inefficiency or an opportunity. (Nor is it simply throwing a suite of AI tools against a data set — these tools can discover patterns and outliers, but still require a human to judge whether a process improvement can be made or a better contract secured.)

Spendata was built as a third generation spend analysis solution where

  • data can be loaded and processed at any point of the analysis
  • the schema is developed and modified on the fly
  • derived dimensions can be created instantly based on any combination of raw and previously defined derived dimensions
  • additional datasets from internal or external sources can be loaded as their own cubes, which can then be federated and (jointly) drilled for additional insight
  • new dimensions can be built and mapped across these federations that allow for meaningful linkages (such as commodities to cost drivers, savings results to contracts and purchasing projects, opportunities by size, complexity, or ABS analysis, etc.)
  • all existing objects — dimensions, dashboards, views (think dynamic reports that update with the data), and even workspaces can be cloned for easy experimentation
  • filters, which can define views, are their own objects, can be managed as their own objects, and can be, through Spendata‘s novel filter coin implementation, dragged between objects (and even used for easy multi-dimensional mapping)
  • all derivations are defined by rules and formula, and are automatically rederived when any of the underlying data changes
  • cubes can be defined as instances of other cubes, and automatically update when the source cube updates
  • infinite scrolling crosstabs with easy Excel workbook generation on any view and data subset for those who insist on looking at the data old school (as well as “walk downs” from a high-level “view” to a low-level drill-down that demonstrates precisely how an insight was found
  • functional widgets which are not just static or semi-dynamic reporting views, but programmable containers that can dynamically inject data into pre-defined analysis and dimension derivations that a user can use to generate what-if scenarios and custom views with a few quick clicks of the mouse
  • offline spend analysis is also available, in the browser (cached) or on Electron.js (where the later is preferred for Enterprise data analysis clients)

Furthermore, with reference to all of the above, analyst changes to the workspace, including new datasets, new dashboards and views, new dimensions, and so on are preserved across refresh, which is Spendata’s “inheritance” capability that allows individual analysts to create their own analyses and have them automatically updated with new data, without losing their work …

… and this was all in the initial release. (Which, FYI, no other vendor has yet caught up to. NONE of them have full inheritance or Spendata‘s security model. And this was the foundation for all of the advanced features Spendata has been building since its release six years ago.)

After that, as per our updates in 2018 and 2020, Spendata extended their platform with:

  • Unparalleled Security — as the Spendata server is designed to download ONLY the application to the browser, or Spendata‘s demo cubes and knowledge bases, it has no access to your enterprise data;
  • Cube subclassing & auto-rationalization — power users can securely setup derived cubes and sub-cubes off of the organizational master data cubes for the different types of organizational analysis that are required, and each of these sub-cubes can make changes to the default schema/taxonomy, mappings, and (derived) dimensions, and all auto-update when the master cube, or any parent cube in the hierarchy, is updated
  • AI-Based Mapping Rule Identification from Cube Reverse Engineering — Spendata can analyze your current cube (or even a report of vendor by commodity from your old consultant) and derive the rules that were used for mapping, which you can accept, edit, or reject — we all know black box mapping doesn’t work (no matter how much retraining you do, as every “fix” all of a sudden causes an older transaction to be misclassified); but generating the right rules that can be human understood and human maintained guarantees 100% correct classification 100% of the time
  • API access to all functions, including creating and building workspaces, adding datasets, building dimensions, filtering, and data export. All Spendata functions are scriptable and automatable (as opposed to BI tools with limited or nonexistent API support for key functions around building, distributing, and maintaining cubes).

However, as we noted in our introduction, even though this put Spendata leagues beyond the competition (as we still haven’t seen another solution with this level of security; cube subclassing with full inheritance; dynamic workspace, cube, and view creation; etc.), they didn’t stop there. In the rest of this article, we’ll discuss what’s new from the viewpoint of Spendata Competitors:

Spendata Competitors: 7 Things I Hate About You

Cue the Miley Cyrus, because if competitors weren’t scared of Spendata before, if they understand ANY of this, they’ll be scared now (as Spendata is a literal wrecking ball in analytic power). Spendata is now incredibly close to negating entire product lines of not just its competitors, but some of the biggest software enterprises on the planet, and 3.0 may trigger a seismic shift on how people define entire classes of applications. But that’s a post for a later day (but should cue you up for the post that will follow this on on just precisely what Spendata 2.2 really is and can do for you). For now, we’re just going to discuss seven (7) of the most significant enhancements since our last coverage of Spendata.

Dynamic Mapping

Filters can now be used for mapping — and as these filters update, the mapping updates dynamically. Real-time reclassify on the fly in a derived cube using any filter coin, including one dragged out of a drill down in a view. Analysis is now a truly continuous process as you never have to go back and change a rule, reload data, and rebuild a cube to make a correction or see what happens under a reclassification.

View-Based Measures

Integrate any rolled up result back into the base cube on the base transactions as a derived dimension. While this could be done using scripts in earlier versions, it required sophisticated coding skills. Now, it’s almost as easy as a drag-and-drop of a filter coin.

Hierarchical Dashboard Menus

Not only can you organize your dashboards in menus and submenus and sub-sub menus as needed, but you can easily bookmark drill downs and add them under a hierarchical menu — makes it super easy to create point-based walkthroughs that tell a story — and then output them all into a workbook using Spendata‘s capability to output any view, dashboard, or entire workspace as desired.

Search via Excel

While Spendata eliminates the need for Excel for Data Analysis, the reality is that is where most organizational data is (unfortunately) stored, how most data is submitted by vendors to Procurement, and where most Procurement Professionals are the most comfortable. Thus, in the latest version of Spendata, you can drag and drop groups of cells from Excel into Spendata and if you drag and drop them into the search field, it auto-creates a RegEx “OR” that maintains the inputs exactly and finds all matches in the cube you are searching against.

Perfect Star Schema Output

Even though Spendata can do everything any BI tool on the market can do, the reality is that many executives are used to their pretty PowerBI graphs and charts and want to see their (mostly static) reports in PowerBI. So, in order to appease the consultancies that had to support these executives that are (at least) a generation behind on analytics, they encoded the ability to output an entire workspace to a perfect star schema (where all keys are unique and numeric) that is so good that many users see a PowerBI speed up by a factor of almost 10. (As any analyst forced to use PowerBI will tell you, when you give PowerBI any data that is NOT in a perfect star schema, it may not even be able to load the data, and that it’s ability to work with non-numeric keys at a speed faster than you remember on an 8088 is nonexistent.)

Power Tags

You might be thinking “tags, so what“. And if you are equating tags with a hashtag or a dynamically defined user attribute, then we understand. However, Spendata has completely redefined what a tag is and what you can do with it. The best way to understand it is a Microsoft Excel Cell on Steroids. It can be a label. It can be a replica of a value in any view (that dynamically updates if the field in the view updates). It can be a button that links to another dashboard (or a bookmark to any drill-down filtered view in that dashboard). Or all of this. Or, in the next Spendata release, a value that forms the foundation for new derivations and measures in the workspace just like you can reference a random cell in an Excel function. In fact, using tags, you can already build very sophisticated what-if analysis on-the-fly that many providers have to custom build in their core solutions (and take weeks, if not months, to do so) using the seventh new capability of Spendata, and usually do it in hours (at most).

Embedded Applications

In the latest version of Spendata, you can embed custom applications into your workspace. These applications can contain custom scripts, functions, views, dashboards, and even entire datasets that can be used to instantly augment the workspace with new analytic capability, and if the appropriate core columns exist, even automatically federate data across the application datasets and the native workspace.

Need a custom set of preconfigured views and segments for that ABC Analysis? No sweat, just import the ABC Analysis application. Need to do a price variance analysis across products and geographies, along with category summaries? No problem. Just import the Price Variance and Category Analysis application. Need to identify opportunities for renegotiation post M&A, cost reduction through supply base consolidation, and new potential tail spend suppliers? No problem, just import the M&A Analysis app into the workspace for the company under consideration and let it do a company A vs B comparison by supplier, category, and product; generate the views where consolidation would more than double supplier spend, save more than 100K on switching a product from a current supplier to a lower cost supplier; and opportunities for bringing on new tail spend suppliers based upon potential cost reductions. All with one click. Not sure just what the applications can do? Start with the demo workspaces and apps, define your needs, and if the apps don’t exist in the Spendata library, a partner can quickly configure a custom app for you.

And this is just the beginning of what you can do with Spendata. Because Spedata is NOT a Spend Analysis tool. That’s just something it happens to do better than any other analysis tool on the market (in the hands of an analyst willing to truly understand what it does and how to use it — although with apps, drag-and-drop, and easy formula definition through wizardly pop-ups, it’s really not hard to learn how to do more with Spendata than any other analysis tool).

But more on this in our next article. For The Times They Are a-Changin’.

1 Duey, Clutterbuck, and Howell keeps Dewey, Cheatem, and Howe on retainer … it’s the only way they can make sure you pay the inflated invoices if you ever wake up and realize how much you’ve been fleeced for …