Monthly Archives: March 2024

Vroozi: Address the Bluesy of your Procurement Problems With a Solution That’s Doozy and Approved by the Choosy! Part 1

Vroozi was founded in 2012 with a vision of building a modern P2P solution that could be used by all organizations and Procurement professionals regardless of where they were and what device they were using — as they were the first P2P platform with a mobile-first philosophy. The goal was to build a solution that was easy to use, automated to the extent possible, collaborative, and easy to adopt by all individuals in the organization that needed to make purchasing requests, do Procurement, give approvals, and make payments. The opposite of the highly manual, closed, and cumbersome first-generation systems that gave their users the City Boy Blues.

They’ve achieved their goal, and then some, with a solution that is enterprise grade but yet priced for the mid-market. Whereas most P2P solutions fall short of payments, they can do payments (with their direct integration into two leading payment platforms) — and they can do invoicing compliant with both post-audit and clearance countries. Whereas most Procurement solutions require you to switch to a sourcing suite for a simple RFQ, they can do RFQs too. Whereas most focus on either internal/hosted or punch-out catalogs, they do both, as well as mixed and templated service offerings — all through a single integrated search that can also take into account enhanced company and product attributes on hosted and mixed catalogs. Whereas most P2P solutions don’t tie to contracts, the Vroozi platform can maintain all appropriate contract metadata to track spending against contracts and budgets. Whereas most have only the minimal supplier details to send the PO and Payment, the Vroozi platform allows for extended data to be maintained to allow for in-depth recommendations during search, straight-through processing rules for invoices when there are minor exceptions, and meaningful reports and analytics. Speaking of analytics, whereas most P2P platforms have limited to non-existent reporting solutions, Vroozi has integrated a reporting package that’s on par with most mid-market Source-to-Contract and P2P suites which provides a decent starting point for many organizations to get a handle on their spending.

Going back to supplier data, Vroozi can integrate with your ERP/MRP/Supplier Master and keep the relevant supplier data current for you — enhancing what you already have. It’s an extensive P2P++ solution that can even negate the need for a sourcing platform in an organization where the majority of purchasing is tactical or of moderate value or less. (If an organization doesn’t have a lot of high spend or strategic categories that need sophisticated sourcing technology with auctions or optimization capability, they can usually do without a dedicated platform and use pay per event solutions like MarketDojo or consultancies with licences. In other words, the only other solution the organization may need is a CLM solution — which only enhances the value of the Vroozi solution.) Also, because it can be opened up to the entire organization, who can have view access into the status of their request and all associated documents at all times, it has intake out of the box. (And because it can connect with relevant enterprise ERP, Finance, and S2C systems, it can serve as the Procurement orchestration platform as well.)


In the Vroozi platform, e-Procurement revolves around purchase requests that come from:

  • catalog search
  • non-catalog requests
  • RFQs

which may or may not be accessed through their SmartChat NLP (Natural Language Processing) tool.

Integrated and Intelligent Catalog Search

In the Vroozi system, a user can do a search across all of their catalogs, whether they are hosted, punch-out, or mixed (as the user can replicate part of a punch-out catalog in the hosted environment to augment and enrich the data with relevant company and product attributes that can aid in not only the search but the ranking and recommendation). The system can support ordered recommendations based on (lowest) cost, contract/preferred status, diversity supplier, or a weighted combination of those and/or other factors.

Search brings up results in a consumer like (Amazon) interface where it’s one click to add to a cart, and one click in the cart to initiate a purchase request. If a user can’t find what they want internally, or prefers a third-party site, one click takes them to the punchout site, and one click in the punchout site (including Amazon [Business]) takes them back to the Vroozi portal to submit the purchase request.

Search can be filtered on all relevant dimensions (supplier, brand, product [sub] category, etc.), which, if the content is hosted, can also include a slew of company attributes and product attributes. Company attributes could include diversity, green certified, preferred contract, premier (off-contract) supplier, IT, MRO, Office Suppliers, and other relevant categories. Product dimensions can include preferred product (off-contract), free shipping, refurbished, warranty, etc.

Non-Catalog Requests

Not all requests are for products found in a catalog. Some are for custom configurations of products where standard configurations are catalog, and some are for relatively standard service offerings that have contract pricing based on easily defined variables or configurations. The Vroozi application can support both of these through extended-catalog and non-catalog requests. If a buyer needs a new laptop with a custom configuration, the system will bring up an item with drop downs and/or special request fields where the user can select the precise configuration she needs. If a buyer needs to request janitorial services for the new, temporary office location, she can bring up the request, specify the required parameters that define the service level (square footage, type of cleaning [one-time or daily/weekly maintenance for a period of time, deep cleaning, etc.], hours it needs to be completed in), and the system will compute the number of people needed and the contract rate. Even complex requests can be completed and submitted quickly and with ease.

Bulk Upload Requests

Vroozi supports the creation of requisitions via extremely simple bulk upload. It can be as simple as a 2-column .CSV file containing Item Id, Quantity rows for basic products in the catalog. In addition, a full SOW (Statement of Work) requisition can also be created simply by specifying the core fields of: Supplier ID, Category ID, GL Account, Item Description, UOM (Unit of Measure), Price, Tax Code, Currency, Start Date, and End Date for each line on the SOW (Statement of Work). All of the appropriate information is automatically pulled in to create a complete requisition, which can be instantly used to generate a PO if the purchaser is buying from approved suppliers/blanket POs within their budget and auto-approval rules.

Next-Gen AI Powered Smart Chat

One of the main selling points of the intake and orchestration platforms getting all the buzz (and all the funding, some to the point where they are going to have to sell the solutions at ridiculous prices to reclaim the investor’s money) is their ability to not only make it super easy for organizational users to make Procurement requests in natural language through an AI chatbot, but an AI chatbot that will ask the right questions to get them to the exact product or service they need and let them put a request in with a single statement or confirmation (“create purchase request” or “yes”), and, in particular, text-based smart chat bots that can be served through an API to another enterprise platform the employees use daily.

Well, guess what? Vroozi has this too! No need for an overpriced “intake” or “orchestration” platform.

The Vroozi Smart Chat Bot is very well designed, and will ask as many questions as needed to get the user to the exact product or service they need. In the laptop scenario, the system will ask for the primary use (business, development, etc.), memory requirement, storage requirement, etc. In the services scenario, it will confirm the user wants janitorial services, confirm the vendor and contract, take the user through the questions, propose the requisition, and automatically create it with a confirmation.


RFQ Functionality in Vroozi is very straight forward. The user simply has to give the request a name and due by date; define the products or services they want by description, part/service number, category, quantity, unit of measure, and delivery date; and select the suppliers from the directory (or create a new ad-hoc supplier; however, no PR or PO can be created without approvals and master data setup if awarded to an ad-hoc supplier). That’s it. Then it’s wait for either all the suppliers to respond or the due date to hit, evaluate, make an award, and (if no ad-hoc suppliers were selected that require approval), create the requisition. (Once the RFQ is created, the suppliers are notified by email, and it’s one-click from the e-mail to go to the bid screen, where they will be required to enter their one-time bid passcode to prevent compromised logins.) Awarding is just a matter of selecting the bid and clicking the award button.

Easy One Click Approvals

Once a purchase request has been created, it goes to the first approver for approval. It gets entered to their queue in the Vroozi application, where they can approve it instantly, and through e-mail, where they can one-click approve or reject it. The click takes them to either a screen that acknowledges their approval, or a screen that acknowledges their rejection where they can input a reason and whether or not the requester can resubmit with a modification. To make the rejection process super easy, the user can select a standard reason for dispute from a drop down and only needs to free-form enter a reason or further explanation in special situations that should not be the norm.

Invoice Management

Vroozi is not just an e-Procurement platform, it’s also an Invoice-to-Pay / Accounts Payable platform with full invoice management capability. The great thing about the Vroozi platform is that it supports super easy PO flip in the portal (as well as allowing vendors to submit invoices in multiple standard encodings), meaning all the data can come in complete, correct, and already matching. They also support PDF (by email) submission, and have the capability to process (relatively) “standard” PDF invoices and auto-extract all the key fields.

Once the invoice is in the queue for processing, the matches are applied, and if they succeed, it goes straight for approvals, and if the invoice is against a blanket PO or contract and in budget, it can be auto-approved and go straight to posting, which can get the Vendor paid fast (and gives the Vendor a reason to use the system). If they fail, then the invoice is stopped for processing. If everything matches and there are blanket POs or contracts and budgets are met, it can be auto-processed and goes straight to the posting queue. If not, it goes out for approval. Once the invoices is stopped for match failures or is deemed to need manual approvals, it stays in the processing queue until it has received any necessary non-AP approvals (which might be required if all invoices above a threshold value or for certain categories must get sign-off even if there is an approved PO) and there is a goods receipt to match against the invoice with the PO for a 3-way match or an AP manager completes exception processing and pushes it to to the processing queue. Once corrected and/or approved, the invoice goes straight to posting. And, of course, the supplier, if they use the portal, sees the current invoice state at all times.

The great thing about the platform is the power that is contained in approval chain creation and management, which can be setup in the same manner as purchase order approval chains if desired. Once an invoice is in the processing queue, if there is a 3-way match, it is automatically processed, and if it matches exactly or within tolerances, it goes straight to posting without any touch. If there is only a 2-way match, and if there are exception rules (for example, services, recurring charges, etc.) that allow 2-way processing, then if there is an exact match or a match within tolerances, it will also go to straight to posting without any human touch.

In other words, in Vroozi, only exception invoices need to be processed, and a single click can reject and flip them back to the supplier (preferably with a reason) or accept them when the variation is acceptable, agreed to, or approved by the buyer (such as a higher price for substitute items when an order was made without the necessary notice). Furthermore, to ensure that exception processing is efficient, the end user organization can define multiple types of exception handlers to ensure that the invoice is routed to the right group when there is an exception. For example, if it’s just a tax issue or an unexpected shipping and/or handling charge, then it can likely be resolved by AP and should go to an AP clerk. But if it’s a unit price issue that doesn’t match the contract, which the supplier is refusing to back down on, it might need to go to Procurement for an exception approval or to Legal who may need to call the supplier and explain what will happen next if the unit price isn’t fixed.

In addition, there are built-in options for auto-processing / auto-return for overcharges. The system can automatically reject the invoice, automatically modify the invoice based on agreed to amounts and then notify the supplier of the changes upon approval, or leave the invoice as is and automatically create a credit memo (and notify the supplier on approval that the credit was applied against this invoice or will be applied against a future invoice at payment time).

Shipping Notices & Good Receipts

The Vroozi platform is capable of accepting and processing shipping notices in the same manner that it receives invoices, and these can even be used in a 4-way match if desired by the system. Shipping Notices and Goods receipts are incredibly easy to create in the Vroozi system. Just like a user can one-click flip a PO to invoice, they can one-click flip a PO to a shipping invoice where all they have to do is verify the line-item quantities. Similarly, a user can one-click “flip” a goods receipt from a PO, shipping notice, or invoice as easy as a supplier can flip a PO into an invoice. All the user has to do is enter the quantity received for each line item and the goods receipt is complete and can be used in the 3-way match for straight through processing. Note that if the organization has turned on the appropriate matching, the users will have to receive goods before the associated invoices can be processed.

3-Way Match and Straight Through Processing

The power of an I2P solution is one that can automate invoice processing touch free and free up valuable Procurement and Accounts Payable time to focus on the exceptions and the issues, and not tactical processing which prevents issues from being resolved, and sometimes even from being detected when an invoice has too many line items for detailed processing and all the AP clerk can do is a rough check on the total amount versus the total expected amount. Also, as it is capable of automatically processing every invoice that comes in, it can identify obvious and potential duplicates, invoices that don’t match a PO, and invoices that are potentially fraudulent and reject them or “quarantine” them for manual review.

Credit Memos

Credit Memos are automatically created during invoice exception handling when the buyer decides that the organization is going to pay the PO price (which usually happens when the organization has a contract or valid commitment that has not yet expired from a previous quote), overrides the invoice price to the PO price, and then approves the invoice, which is queued for payment at the adjusted amount captured in the (automatically generated) credit memo that is sent to the supplier. The supplier gets the credit memo in their portal, as well as a status change that informs them that the buyer adjusted invoice has been approved for payment.

Come back tomorrow where we will continue our discussion of the Vroozi P2P++ offering, including Payments, the Supplier Directory, Analytics, Platform Administration, and the Supplier Portal.

You Don’t Need Gen-AI to Revolutionize Procurement and Supply Chain Management — Classic Analytics, Optimization, and Machine Learning that You Have Been Ignoring for Two Decades Will Do Just Fine!

Open Gen-AI technology may be about as reliable as a career politician managing your Nigerian bank account, but somehow it’s won the PR war (since there is longer any requirement to speak the truth or state actual facts in sales and marketing in most “first” world countries [where they believe Alternative Math is a real thing … and that’s why they can’t balance their budgets, FYI]) as every Big X is pushing Open Gen-AI as the greatest revolution in technology since the abacus. the doctor shouldn’t be surprised, given that most of the turkeys on their rafters can’t even do basic math* (but yet profess to deeply understand this technology) and thus believe the hype (and downplay the serious risks, which we summarized in this article, where we didn’t even mention the quality of the results when you unexpectedly get a result that doesn’t exhibit any of the six major issues).

The Power of Real Spend Analysis

If you have a real Spend Analysis tool, like Spendata (The Spend Analysis Power Tool), simple data exploration will find you a 10% or more savings opportunity in just a few days (well, maybe a few weeks, but that’s still just a matter of days). It’s one of only two technologies that has been demonstrated, when properly deployed and used, to identify returns of 10% or more, year after year after year, since the mid 2000s (when the technology wasn’t nearly as good as it is today), and it can be used by any Procurement or Finance Analyst that has a basic understanding of their data.

When you have a tool that will let you analyze data around any dimension of interest — supplier, category, product — restrict it to any subset of interest — timeframe, geographic location, off-contract spend — and roll-up, compare against, and drill down by variance — the opportunities you will find will be considerable. Even in the best sourced top spend categories, you’ll usually find 2% to 3%, in the mid-spend likely 5% or more, in the tail, likely 15% or more … and that’s before you identify unexpected opportunities by division (who aren’t adhering to the new contracts), geography (where a new local supplier can slash transportation costs), product line (where subtle shifts in pricing — and yes, real spend analysis can also handle sales and pricing data — lead to unexpected sales increases and greater savings when you bump your orders to the next discount level), and even in warranty costs (when you identify that a certain supplier location is continually delivering low quality goods compared to its peers).

And that’s just the Procurement spend … it can also handle the supply chain spend, logistics spend, warranty spend, utility and HR spend — and while you can’t control the HR spend, you can get a handle on your average cost by position by location and possibly restructure your hubs during expansion time to where resources are lower cost! Savings, savings, savings … you’ll find them ’round the clock … savings, savings, savings … analytics rocks!

The Power of Strategic Sourcing Decision Optimization

Decision optimization has been around in the Procurement space for almost 25 years, but it still has less than 10% penetration! This is utterly abysmal. It’s not only the only other technology that has been generating returns of 10% or more, in good times and bad, for any leading organization that consistently uses it, but the only technology that the doctor has seen that has consistently generated 20% to 30% savings opportunities on large multi-national complex categories that just can’t be solved with RFQ and a spreadsheet, no matter how hard you try. (But if you want to pay them, a Big X will still claim they can with the old college try if you pay their top analyst’s salary for a few months … and at 5K a day, there goes three times any savings they identify.)

Examples where the doctor has repeatedly seen stellar results include:

  • national service provider contract optimization across national, regional, and local providers where rates, expected utilization, and all-in costs for remote resources are considered; With just an RFX solution, the usual solution is to go to all the relevant Big X Bodyshops and get their rate cards by role by location by base rate (with expenses picked up by the org) and all-in rate; calc. the expected local overhead rate by location; then, for each Big X – role – location, determine if the Big X all-in rate or the Big X base rate plus their overhead is cheaper and select that as the final bid for analysis; then mark the lowest bid for each role-location and determine the three top providers; then distribute the award between the three “top” providers in the lowest cost fashion; and, in big companies using a lot of contract labour, leave millions on the table because 1) sometimes the cheapest 3 will actually be the providers with the middle of the road bids across the board and 2) for some areas/roles, regional, and definitely local, providers will often be cheaper — but since the complexity is beyond manageable, this isn’t done, even though the doctor has seen multiple real-world events generate 30% to 40% savings since optimization can handle hundreds of suppliers and tens of thousands of bids and find the perfect mix (even while limiting the number of global providers and the number of providers who can service a location)
  • global mailer / catalog production —
    paper won’t go away, and when you have to balance inks, papers, printing, distribution, and mailing — it’s not always local or one country in a region that minimizes costs, it’s a very complex sourcing AND logistics distribution that optimizes costs … and the real-world model gets dizzying fast unless you use optimization, which will find 10% or more savings beyond your current best efforts
  • build-to-order assembly — don’t just leave that to the contract manufacturer, when you can simultaneously analyze the entire BoM and supply chain, which can easily dwarf the above two models if you have 50 or more items, as savings will just appear when you do so

… but yet, because it’s “math”, it doesn’t get used, even though you don’t have to do the math — the platform does!

Curve Fitting Trend Analysis

Dozens (and dozens) of “AI” models have been developed over the past few years to provide you with “predictive” forecasts, insights, and analytics, but guess what? Not a SINGLE model has outdone classical curve-fitting trend analysis — and NOT a single model ever will. (This is because all these fancy-smancy black box solutions do is attempt to identify the record/transaction “fingerprint” that contains the most relevant data and then attempt to identify the “curve” or “line” to fit it too all at once, which means the upper bound is a classical model that uses the right data and fits to the right curve from the beginning, without wasting an entire plant’s worth of energy powering entire data centers as the algorithm repeatedly guesses random fingerprints and models until one seems to work well.)

And the reality is that these standard techniques (which have been refined since the 60s and 70s), which now run blindingly fast on large data sets thanks to today’s computing, can achieve 95% to 98% accuracy in some domains, with no misfires. A 95% accurate forecast on inventory, sales, etc. is pretty damn good and minimizes the buffer stock, and lead time, you need. Detailed, fine tuned, correlation analysis can accurately predict the impact of sales and industry events. And so on.

Going one step further, there exists a host of clustering techniques that can identify emergent trends in outlier behaviour as well as pockets of customers or demand. And so on. But chances are you aren’t using any of these techniques.

So given that most of you haven’t adopted any of this technology that has proven to be reliable, effective, and extremely valuable, why on earth would you want to adopt an unproven technology that hallucinates daily, might tell of your sensitive employees with hate speech, and even leak your data? It makes ZERO sense!

While we admit that someday semi-private LLMs will be an appropriate solution for certain areas of your business where large amount of textual analysis is required on a regular basis, even these are still iffy today and can’t always be trusted. And the doctor doesn’t care how slick that chatbot is because if you have to spend days learning how to expertly craft a prompt just to get a single result, you might as well just learn to code and use a classic open source Neural Net library — you’ll get better, more reliable, results faster.

Keep an eye on the tech if you like, but nothing stops you from using the tech that works. Let your peers be the test pilots. You really don’t want to be in the cockpit when it crashes.

* And if you don’t understand why a deep understand of university level mathematics, preferably at the graduate level, is important, then you shouldn’t be touching the turkey who touches the Gen-AI solution with a 10-foot pole!

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 …

The Best Way Procurement Chiefs Can Create a Solid Foundation to Capitalize on AI

As per our recent post on how I want to be Gen AI Free, the best way to capitalize on Gen-AI is to avoid it entirety. That being said, the last thing you should avoid is the acquisition of modern technology, including traditional ML-AI that has been tried and tested and proven to work extremely well in the right situation.

That being said, if you ignore the reference to Gen-AI, a recent article on Acceleration Economy on 5 Ways Procurement Chiefs Can Create a Solid Foundation had some good tips on how to go about adopting ML-AI with success.

The five foundations were quite appropriate.

1. Organize

A plan for

  1. exactly where the solution will be deployed,
  2. what use cases it will be deployed for,
  3. how valid use cases will be identified, and
  4. how the solution is expected to perform on them.

There’s no solution, even AI, that can do everything. Even limited to a domain, no AI will work for all situations that may arise. As a result, you need a methodology to identify the valid use cases and the invalid use cases and ensure that only the valid uses cases are processed. You also need to ensure you know the expected ranges of the answers that will be provided. Then you need to implement checks to ensure that no only are only valid situations processed but that only output in an expected range is accepted in any automated process, and if anything is outside the expected norms anywhere, a human with appropriate education and training is brought into the loop.

2. Create a Policy

No technology should be deployed in critical situations without a policy dictating valid, and invalid, use. Moreover, any technology definitely shouldn’t be used by people who aren’t trained in both the job they need to do and proper use of the tool. Even though most AI is not as dangerous as Gen-AI, any AI, if improperly used, can be dangerous. It’s critical to remember that computers cannot think, and only thunk on the data they are given (performing millions of calculations in the time it takes an average person to perform two). As such, the quality of output is limited both to the quality of data input and the knowledge built into the model used. Neither will be complete or perfect, and there will always be external factors not considered, which, even if normally not relevant, could be relevant — and only an educated and experienced human will know that. (Moreover, that human needs to be involved in the policy creation to ensure the technology is only used where, when, and how appropriate.)

3. Understand Your Platform(s) of Choice

Just like there are a plethora of Gen-AI applications, a lot of different vendors offer AI applications, and even if most are similar, not all are created equal. It’s important to understand the similarities and differences between them and select the one that is right for your business. (Consider the algorithms and models used, the extent of human validated training available, typical accuracy / results, and the vendor’s experience in your use case in particular when evaluating an AI solution.)

4. Practice

Introducing new tools requires process changes. Before introducing the tool, make sure you can execute the associated process changes, first by executing training exercises on the different types of output you might get and then, possibly by way of a third party who uses a tool on your behalf, using real inputs and associated outputs. While the AI may automate more of the process, it’s even more critical that you respond appropriately to parts of the process that cannot be automated or where the application throws an exception because the situation is not appropriate to either the use of AI or the use of the AI output. (And if you don’t get any exceptions, question the AI … it’s not likely not working right! And if you get too many exceptions, it’s not the right AI for you.)

5. ALWAYS Ask Yourself: “Does that Make Sense?”

Just like Gen-AI hallucinates, traditional AI, even tried-and-true AI that is highly predictable, will sometimes give wrong results. This will usually happen if bad data slips in, if the use case is on the boundary of expected use cases, or the external situation has changed considerably since the last time the use case arose. Thus, it’s always important to ask yourself if the output makes sense. For tried-and-true AI where the confidence is high, it will make sense the vast majority of the time, but there will still be the occasional exception. Human confirmation is, thus, always required!

With proper use, AI, unlike Gen-AI (which fails regularly and sometimes hallucinates so convincingly that even an expert has a hard time identifying false results), will give great results the majority of the time — so you should seek it out and implement it. Just also implement checks and balances to catch those rare situations it doesn’t and put a human in the loop when that happens. Because traditional use-cases are more constrained, and predictable, it’s a lot easier to identify and implement these checks and balances. So do it … and see great success!

Tonkean: Making Enterprise Procurement work with ProcurementWorks, Part 2

In Part 1, we introduced you to Tonkean, an enterprise applications provider founded in 2015 to transform the enterprise back office. Tonkean leverages smart technology to bring people, process, and technology together in a manner that revolutionizes how businesses operate, allowing people to focus on high value work that gets results, and not redundant data processing, unnecessary application usage (which requires unnecessary training and unnecessary time), or unnecessary emails. The primary goal is to increase adoption and push employee requests, and actions, through official channels, instead of having enterprise employees find backdoors and dark hallways to get around cumbersome systems and processes they don’t want to use.

After providing a brief history and an overview, most of Part I focussed on Tonkean’s AI Front Door, a smart AI interface that was built by a team that understands the strengths, weaknesses, and, most importantly, the limits of AI, especially LLMs and (Open) Gen AI, and that includes pre- and post- processing to verify the requests and responses as reasonable, and where confidence is lacking, not provide any response (and send the inquiry, and response, or lack thereof, for a human who can, if necessary, tune the underlying system after review).

Today we will overview the rest of the Tonkean Intake Orchestration Platform for Procurement and how it can help your organization.

Procurement Intake and Guided Buying

The core of ProcurementWorks is their intake ability described above and guided buying that gets a requester to the right process and form and allows them to monitor, take part in, and/or execute the process end-to-end as required. They can do this through their platform, via e-mail, or a third party platform, like Slack or Microsoft Teams, through their integration capability. If the buy is small and can be put on a PCard, the system will direct the user to do so. If it’s large and requires a buyer to run a Procurement event, the system will guide the buyer to provide all the information the buyer needs and provide updates to the requester after each step of the process is concluded (which the buyer can proactively monitor through the ProcurementWorks request tracking application that monitors the entire workflow, which can be as simple as the request, Procurement approval, and PO/contract generation or as involved as a request, budgetary approval, procurement acceptance, RFX, award selection, InfoSec Approval, Risk & Compliance approval, Legal approval, contract generation, contract negotiation, signing, and completion).

All of this can be done in the Tonkean platform if desired, which will integrate with, push data into, and pull data out of any enterprise applications that are used for Finance, Procurement, Risk, Legal, and Contracts. For example, the system can pull the associated budget for the category from the budget system and send the appropriate manager the request for approval based on the expected cost and the category budget. If approval to proceed is received, the buyer can setup an RFP, which can then be pushed into the enterprise’s sourcing platform (which could be Coupa or Ariba) for execution, and then the results pulled back into the Tonkean request tracking and management module. Procurement can then select one, send it off to InfoSec, Risk, and Legal, in order, for approval, which can come in through the platform, and, once received, use the platform to push the award details into the CLM that can generate the contract, which the platform can then push to the supplier for signature through their e-Signature platform, and when it’s signed, push it back into the CLM.

The platform comes with a number of built-in Procurement process templates that can be customized as needed to support every organizational category and buying process based upon organizational needs. It can be integrated with all the applications and all the document stores, pull in the necessary attachments, help with exchange and version management, and track approvals. And it can be accessed through the form based interface or the chatbot, natively or through API connections.

Procurement Center (Workspace Apps)

The enterprise can create multiple views (and even multiple, separate portals if they like) to support both the Procurement Team and the employees that need to interact with Procurement (so that Legal, Risk & Compliance, IT/InfoSec can all have their own views, and even their own portals if they want to handle their workflows through Tonkean versus their current applications). (Thus, in addition to the Procurement Request Tracker and Manager, Procurement could build a custom Risk and Compliance Portal, Contract Negotiation Tracking and Management Portal, Vendor Inquiry Portal, and so on.)

How little or how much is enabled by default in the Procurement Center is up to the customer, but typically the Procurement Center will contain:

  • AI Front Door: Their name for their AI request intake experience, which can process free text requests or guided requests based on drop downs
  • My Requests: A listing of all of the users’s requests where they can click into the Request Tracker (which listens in near real time for system updates from all integrated systems)
  • My Approvals: A listing of all of the approvals and reviews in the user’s queue (that other users are waiting on)
  • Reporting Dashboards: Tonkean is not a BI/Analytics platform (and integrates with yours for deep Analytics/BI), but comes with a number of out of the box templates for workflow/process/cycle time analysis, request tracking, review and approval tracking, supplier onboarding/review request tracking, sourcing request tracking, invoice monitoring, etc. and can build custom dashboards by role (CPO, CFO, etc.) and pull in data from the connected BI systems to populate those dashboards if desired
  • My Supplier Requests: A listing of the suppliers that the user has requested be onboarded, where they can click into the New Supplier Tracker that tracks the pre-onboarding and onboarding steps that must be completed for the supplier to be onboarded in the Supplier Master (with workflows that adapt to the supplier type; a software vendor offering a product that processes financial or personal data needs considerably more reviews than a new office supplies or janitorial supplies vendor)
  • Solutions Studio: where the super/admin user can update the workflow for the request tracker and all other modules in the system

Reports and Dashboards

As indicated above, there are a number of out-of-the-box reporting templates for Procurement that are easily instantiated/modified in the Tonkean platform. These include, but are not limited to:

Purchase Agreements
The Purchase Agreements Dashboard will summarize, by quarter or month, the number of requests, completed requests, total spend, average completion time for each step (FP&A Review, Management Review, Security Assessment Review, Legal & Privacy Review, IT Review, and Accounting Review, etc.), active requests by status, vendors, spend by vendors, and other key agreement metrics.
New Suppliers
The New Suppliers Dashboard will summarize the number of new supplier requests that came in, the suppliers in each state (NDA Sent, NDA Completed, InfoSec Review, Approved for Onboarding, Profile in Process, Approved, Onboarded in SIM, etc.), and allow a user to click in and see who the suppliers are in each state, who the requester/owner is, and other key data or flags as desired.
Existing Suppliers
The existing suppliers dashboard tracks all suppliers with contracts, insurance, certifications, etc. expiring in the next 90 days where something needs to be done.
CFO Dashboard
The CFO Dashboard will generally contain an overview of spend by quarter/year, compliance, overall productivity, productivity by stakeholder, cycle time by process, workload by buyer/analyst, etc. and other key metrics pulled in from the other reports.

Solutions Studio Module Builder

The core of the Tonkean Enterprise offering is the Solutions Studio that is used to create the no-code workflows from action blocks, triggers, and conditional checks. Action blocks tend to fall into coordination actions (which require people) or workflow (which connect coordination actions and data blocks). Conditional logic make it easy to define requests for information, status, and action items; respond, send updates, and provide notifications; and create approval cycles and assign owners. Workflows make it easy to update data fields, create new (instances of) data objects, trigger module actions, perform (textual) analyses and extract text, create models, train models, and introduce programmatic delays or waits (for information from parallel workstreams, for example).

Data actions provide the means to create, read, update, and delete as applicable (according to the principles of least access required, which will be configured by the Tonkean team on implementation so that any data that should only be capable of being changed in a base system will not be capable of being changed through Tonkean regardless of the user’s authority level) the relevant data in the connected source systems. There are blocks for each system that make it easy to drill in and work with the data in that system, as each data source is preconfigured with the default actions it supports.

For one of the 100+ systems already natively integrated with Tonkean, adding the system as a data source is simply a matter of providing maybe a few connection parameters, and the data source will be good to go for your team, with all of the standard actions available. In the Enterprise Component Manager, it’s easy to drill in and find out, for each data source, the inputs it will accept, the outputs and actions the interface supports, the data retention and audit policies, the access rights, and admins and owners, and general information on connectivity restrictions. It’s also easy to drill into the Tonkean access log and see a complete history and to drill into the data through the Tonkean app (so you don’t have to go to the native app to see what’s available in each object/record, how complete those objects/records usually are, etc. or do low-level SQL queries in the underlying database).

In addition, super users and admins can also define new custom actions if their implementation supports additional data or actions, or they want to define custom actions with more limited capability or complex actions that ensure a sequence of actions (such as updates) happen all-or-nothing. All they have to do is define the action type (Get, Post, Put, Patch, etc.), the URL, the data encoding format, the relevant field(s), and the relevant data and the platform creates the workflow logic for them.

Building the workflow is easy in their graphical select drag-and-drop environment where action blocks and data sources can be dropped and connected by arrows that can encapsulate the associated conditional logic for sequential and parallel workflows.

Procurement Knowledge Base / Component Library

The ProcurementWorks solution can also be configured to support the procurement knowledge base, either by housing documents natively, linking to relevant repositories, or both, allowing for Tonkean intake to also sere as the help center as well as the purchasing request center.

In addition, the Tonkean Component Library contains a large number of standard, out of the box, workflows with embedded standard/best practice, for Procurement, Legal, Compliance and other standard enterprise functions that the customer organization can enable and customize as desired in the Solutions Studio. With Tonkean, an organization doesn’t have to start from scratch, and Tonkean will help the organization pre-configure all of the modules/workflows of interest on go-live.

Data Source (& Communication Platform) Management

The Tonkean platform makes it easy to manage organizational data sources. It’s easy to query which sources exist, what data they have, where they are used, what data can be retrieved, which data can be updated, and what the Tonkean access policies are. Similarly, one can manage which communication platforms are integrated and what they can be used for.

In addition, for each connected data source, Tonkean can provide you a “native” view into the core application and data if you so desire. Want to query your Coupa invoices natively in Coupa? No problem! Tonkean can bring up the appropriate screen from Coupa in a frame where you can see exactly what invoices are there and their status. Want to see the full ticket created in JIRA for the IT Review Team? No problem! Tonkean can pull up the Read-Only JIRA screen for your perusal. It truly is people coordination and enterprise platform orchestration.

In conclusion, if you are a large midsize or global enterprise and have an adoption problem, are struggling to get the value out of your enterprise systems, or are looking for ways to make the whole greater than the some of its parts, and need a better intake platform to boot, consider including Tonkean in your evaluation. They just might be what you need to take your current enterprise software investments to the next level.