Long time readers will know that Sourcing Innovation has been covering the plight of the Oompa Loompas ever since some of them gave up chocolate for code (at Coupa). And it hasn’t been good. Fifteen years ago there was E. Coli at the Nestle Plant (link). Five years ago, there was potential Hepatitis A contamination with Kentucky QVC Chocolate (link). Today, Lindt is facing a lawsuit over lead levels. (Source)
Hopefully some day they can go back to Chocolateering in peace.
Especially Gen-AI? For the longest time, the doctor couldn’t understand why so many Big X consultancies were training so many “consultants” on AI, especially Gen-AI. Most of their junior “consultants” can’t even use advanced functionality in today’s analytics applications (as you need advanced degrees in mathematics, computer science, data science, and/or Operations Research to do so) or deliver significant value on traditional analytics and advisory projects relative to the price they charge (unless they are being led by a more senior person with the analytics knowledge and real-world experience). (Read our previous articles and comments on where this talent ends up [which is typically not a Big X] and where these Big X firms offer unparalleled value [and where you should be using Big X].)
But it was recently all made clear to me. These consultants, who struggle with basic projects (as reflected in the high tech failure rates they are regularly a part of as the typical first choice for a third party implementation team when the vendor does not provide them adequate training and support on the platform they are implementing), are barely up to doing the work (as they are usually straight out of school with no real world experience or deep knowledge of anything not taught in a textbook MBA program), and definitely not up to doing strategic engagements out of the gate!
However, with companies wanting to rapidly digitize across the board (which they need to, but, not all digitization requirements should have equal priority), they need strategic advice and direction, and these firms just don’t have enough senior consultants to handle all the engagements and, most importantly, do the work required to put those book-sized briefs and presentations together.
But the one thing Gen-AI can do is take in millions of pages of strategic plans and presentations, take in instructions of what is desired, then generate pages of text from bits and pieces of these historical plans and presentations for each instruction, amalgamate them all together, and produce a detailed report and presentation that they can present to the client. And do this in a few hours under the guidance of a junior analyst with a (Gen-) AI playbook! Then all the senior person has to do is a quick tweak and review!
We’re not joking! The crazy thing is, with so much free material on the internet, with a little bit of elbow grease, and some very creative prompt engineering, you can do this yourself. And someone on LinkedIn already showed you how — giving you this information for FREE in this LinkedIn article. (And should that article disappear, here’s a link to the author’s article on his site.)
So now you know. It’s not about getting you better results (which may or may not happen, every project is different), it’s to give them the ability to take on more projects that they wouldn’t otherwise have the manpower to do.
And if you really want good results, note that you can always hire a real strategic senior consultant from a specialist niche consultancy who often won’t be on multiple projects at the same time, and who can give the insights you need without wasting trees printing out book sized presentations for you. After al, relative to the value the right consultant will bring, Consultants are Cheap and, in our space, the key to Affordable RFPs!
By now you know our stance on Gen-AI (and how it should be relegated to the rubbish heap from which it came) because it’s not about “AI”, it’s about outcome. And outcome requires a real, predictable, usable solution that helps Human Intelligence (HI!) make the right decision. Such a solution is one that uses tried and true algorithms that support tried and true processes that provide a human with the insight needed to make the right decision at the time, every time a decision needs to be made.
This requires a solution that walks the human user through the process, step by step, and presents them with the information required to make a decision as to whether to progress to another step, what the next step is, and any conditions that need to be put on that next step. This requires a solution that automatically runs all of the typically relevant analysis, on all of the available data, and presents the insight, along with any typical decisions (as [a] default recommendation[s]) made on any similar situations that can be found in the organizational history.
Automation should only occur in situations the organization has defined as acceptable according to well defined, human reviewed, and verified rules. Not default vendor rules or unverified probabilities or unverified random computations from a random algorithm. A good solution is one that walks a user through the process, often allowing each step to be completed with a single choice or click. It’s not one that makes the choice for the user, which may or may not be the right one, but one that helps the user makes the right choice. It might seem like a subtle difference, but it is a very important one.
Even though an AI-powered autonomous solution might seem to make the right decision over 90% (or 95%) of the time, it doesn’t mean it actually is. If it looks right, it might be a good decision, but it doesn’t mean it’s a good decision for the organization at the time, or the best decision that can be made. Only human review, at the time, can make that decision. A good solution runs all the analysis it can, summarizes the results, and lets a human verify the data for any recommendation made by the system.
To better understand the the subtlety, consider a situation where the organization lets the system automatically re-auction all regularly purchased products and commodities for manufacturing or MRO where the price is typically constant over time using a lowest bidder takes all e-Auction that results in the auto-generation and auto e-Signature of a one year contract. Now, most of the time this is probably going to work okay, but imagine you let it run on full auto-pilot and in the e-Auction queue is your regular RAM contract that expired three days after a major RAM plant factory fire (that happens about once every decade if you trace back through the last forty years), and prices have just skyrocketed about 50%. Prices which would drop back down as soon as the plant comes back online in three months. Locking in a full year contract would result in excessive cost overruns on the items for almost nine months longer than necessary, instead of just three months or so. A human would know to buy the bare minimum on the spot market at overly inflated rates and wait until the market stabilized before running an e-Auction to lock in the next contract. But a system told to just re-auction and re-order at every contract expiration would do this that. It wouldn’t know that the current market rates are just temporary, why, and how to change course. This is just one example where over-automation and AI will lead to failure without Human Intervention.
A good system presents the user with the products/commodities that are typically automatically auctioned, the history of costs, the current market costs, the recommendation for auto-sourcing and term, the expected results, and whether the recommendation is for the auction to auto-award and contract or, when the auction is complete, pause and include a human in the loop to make a final decision. A well designed system minimizes the work and input required by a human, eliminating all the tactical data analysis and e-paperwork, making it easy to make the right strategic decision without a lot of effort. Technology isn’t about trying to replace human intelligence (which it can’t), but about eliminating unnecessary drudgery or computation (“thunking”) that humans are not good at (or don’t have the time for), so that humans can focus on strategic decisions and value add.
That’s why the right answer is always a solution with augmented intelligence. Not autonomous AI solutions.
One of the downsides of the Gen-AI mania is the constant messaging that everything is complicated and the only technology that can make it easy is over-engineered, power hungry, planet killing, Gen-AI technology that has to consume mountains of data, be fed by carefully crafted creative prompts (that can take hours, days, and even weeks of trial and error to get right), and require mountains of effort to acquire, install, train, and tweak such a system. The claims are that only this technology can solve modern Procurement problems, when nothing could be further from the truth.
The reality is that not all problems require complex solutions. Some require very simple solutions. India recently provided us with an example of that. In a recent article on how Farmers can use WhatsApp for Paddy Procurement, India presented a rather simple solution to its Paddy Procurement problem, where it needed to simplify the acquisition of rice.
When a large amount of product needs to be procured in a whole lot of small batches, coordination is not easy, especially from suppliers who don’t have the same modern tech. Now, imagine your suppliers are not corporations, but small farms where the most advanced tech might be the cell phone they are holding to make calls. As a result, they don’t have any complicated sales and order management systems, no ability to process XML or EDI, and even using a sophisticated portal on a small screen is a challenge (even if they have a fairly modern smartphone).
However, they have WhatsApp, so the state government has adopted a methodology to support the farmers selling their wares through that platform. When they are ready to sell, all they have to do is text “hi” to a given number, enter their Aadhaar (ID) number, the nearest procurement center, and the number of bags they want to sell. The platform will then provide them with three dates and times, they choose one, and they can then show up, and, without waiting, deliver their bags and get promptly paid. Before, they might have had to wait hours (or all day) if they just showed up, and much longer for payment. Moreover, due to the efficiencies they’ve introduced and other related Procurement efficiencies, the government is able to offer farmers tarpaulin sheets to protect field stock at a 50% subsidy price.
Simple works. Never forget it, and you’ll go further than if you blindly adopt over-promised solutions that under-deliver.
e-Sourcing is a critical part of proper strategic procurement, but one that not a lot of SMEs and lower-end mid-markets have access to due to the cost of most strategic sourcing suites designed for the upper mid-market and enterprise that are beyond their budget, typically leaving them with only ultra-basic RFX solutions which are not enough.
In contrast, oboloo offers a Source-to-Contract platform with basic supplier management, contract document management, and savings management capability which can be obtained for $1,000 / user / year, allowing a SME Procurement department of 5 users to obtain decent sourcing software for 5K a year and put it on a P-card.
e-Sourcing
Their new, V2, e-Sourcing module is the core of the recently upgraded platform and allows an organization to build and issue RFIs, RFPs, and RFQs custom tailored to their needs for every event.
The entry dashboard to the Sourcing module allows a user to search the sourcing event database by opening and / or closing date, location, department, category, sub-category, event type, and event creator. From this dashboard, the user can access an existing event they have access to or create a new event.
If they choose to create a new event, they start with the sourcing wizard that allows them to configure the RFX event as a collection of (pre-defined) (standard) sections for internal use, standard information gathering (supplier questionnaires), event specific supplier sections, and a pricing section. (There’s only one standard product/item pricing template at the moment, but they are looking at including more for services [based on rate hours] and/or [manufacturing] cost breakdowns in future releases. If the user desired a more detailed price breakdown, they can attach an Excel spreadsheet.)
The platform walks the buyer through the process of
Internal sections might consist of information on evaluation criteria and current pricing and cost structures.
Supplier sections consist of relevant criteria on required confidentiality, contact information, implementation plans, and future roadmap. Once a section is selected, it can be edited as needed.
Questionnaires are for the gathering of standard security and privacy information, sustainability information, service and support information, quality assurance, and other standard information required of any supplier for the product, category, or doing business requirements.
The pricing section is where the products are defined, by name, code, unit of measure, and quantity. The buyer can add as many products as she wants.
Once the products are defined, the buyer moves on to the scoring section where she defines the weighted scoring across each section included in the RFX.
Finally, the user selects the suppliers she wants to send the RFX to as well as the contacts at each supplier who will receive the RFX. If she chooses, she can switch to a supplier view before issuing the RFX. When she’s done, she presses send, and the RFP is complete.
The whole process can be completed in 10 minutes if the products are defined in the system and the buyer is okay with standard templates.
With regards to the construction process, the platform comes with a suite of standard sections and questionnaires that the buying organization can start with, and then the buying organization administrator can alter these as desired upon implementation.
Once the RFX is complete, and issued, the buyer can easily access the current status at any time. They can see which suppliers have responded, what they have responded to, and where the RFX is in the process. Once the RFX is closed, the buyer can start scoring and once scoring is complete, make an award.
Scoring is done on a section by section basis, with the information for each supplier displayed in consecutive rows for each supplier. The platform supports multiple scorers, and the weighted average will be used across scorers if multiple scorers are defined. Once scoring is done, the buyer sees the average score by section by supplier as well as the average score by supplier and can then mark a supplier for the award.
Contract Management
oboloo defines their contract management as a customized document management system, and that’s essentially what it is. It’s simply a repository for tracking organizational contracts, indexing them with metadata, defining relevant dates and alerts, and providing some basic reporting. But for most small organizations, that’s all they really need. They don’t use complicated contracts, they don’t want a separate document management system they won’t use, and they certainly don’t need the ability to define extensive clause libraries with multiple versions of each clause.
With respect to reporting, the system tracks expiring contracts by month, and can break them down by department, location, category, manager, type, etc. The user can also search across all of these criteria to quickly identify contracts of interest. It also tracks the number of documents (not) approved, the number of documents that have expired, and the number of contract records associated with suppliers that have been marked approved. And, of course, it can be setup with automated alerts/notifications to let the buyer know when contracts are coming up for expiry, when they are expired, etc. (And, of course these alerts/notifications exist throughout supplier management, RFX, and savings tracking when tasks are due.)
Each contract is a record consisting of key metadata classifiers, owners, financials, termination information, associated information, savings tracking, and a change log.
Supplier Management
The platform is defined as a basic supplier information and performance management platform that can maintain records for all suppliers used, or invited, by the buying organization and these can be searched by key identifiers that include industry, sub-industry, supplier type, preferred status, location, active (status), and contract as well as supplier name.
Supplier records are rather basic and consist of basic identifying information, owners, contacts, contracts, and scorecards. Performance management is scorecard centric in the application, and scorecards are also used to manage risk and track sustainability in the platform, as the buying organization can start with oboloo templates and set up their own to track the information they are interested in from a supplier performance management perspective.
Like contract management it is also fairly basic, but that’s what most SMEs and small midsized organizations need. Most of them don’t need extensive records on suppliers they are mainly buying indirect and MRO products from, and performance management is just a matter of ensuring quality, timely delivery, sustainability, low risk, and adherence to contract(s). This makes it easy for the buying organization to define and manage their suppliers.
Savings Tracking
Savings tracking is a simple module where, on a product, or contract, basis, a buyer can setup a savings tracking project on a fixed or variable time period for a set number of milestone dates. The buyer defines the product(s), current baseline spend (adjusted for the quantity, the projections, and then, at every milestone, defines the actual spend and the platform automatically computes the savings (or the lack thereof) and, once the last milestone is entered, computes the savings for the project.
As with the contract module, the system can then create meta-reports across all savings projects by month, year, and all time, as well as the remaining projected savings (and percentage). This can be broken down by category, sub-category, location, department, saving project type, and the responsible buyer.
Configuration
The platform supports roles-based security, comes with four pre-defined roles, and more can be configured to define created, read, edit, approval, archive, and similar rights across each module. Each user has a role as well as a unique profile.
It also supports the ability to define the industry and sub-industry hierarchy, the category and product hierarchy, corporate locations, departments, and each element type used by the system as identifying metadata (such as sourcing, contract, supplier, saving, document, etc. type). In addition, all of this information can be uploaded from excel (csv). The backend is built on APIs and the next version will have well-defined open APIs for data import as well as third party software integrations by 2025 Q1. Finally, users can select their currency (and define their preferred exchange rate) as well as their language, with approximately 15 languages currently supported.
Finally, the user can see their current licence and the corporate administrator can see all the currently active user licenses on the platform.
At the end of the day, oboloo contains the basic functionality you found in best-in-class first generation sourcing platforms almost two decades ago, with a few key differentiators. It’s a fully modern cloud-native SaaS stack, which can be fully self-implemented and self-configured, with a streamlined UX for SMEs, fully customizable template sections to allow for supplier records, contracts, RFXs, and savings projects to be created in minutes (vs hours or days). Most importantly, all of this comes at a cost that is a fraction of what these early SaaS platforms used to cost (and of what most [mini-]suites targeted at large mid-market and above, with a lot more bells and whistles than SMEs need, cost today), allowing a small sourcing team to get started for under 10K instead of having to spend 100K or more.