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.
We’ve read the dumb company: how to avoid the fork in the road (part 1 and part 2) and dead company walking: avoiding the graveyard (part 1, part 2, part 3, part 4, part 5, part 6, part 7 and part 8) articles, and the two installments of “we want to be a smart company” (part 1 and part 2), and we truly want to be a smart company, and we are taking the mistakes, and advice, to heart. Is there anything else we can do?
There’s always more you can do! However, there’s not much left to talk about that’s true across the board for all software companies. That being said, we can give you ten final pieces of advice that just may help if money is tight, leads are few, and sales are hard. Today, we’ll give you the first five.
01. Don’t Put Off Improvements / Hard Decisions You Know You Need to Do / Make
Fixing it later always takes longer than you think, and the timeframe multiplies the longer you wait! If you need to rip and replace part of the platform core for scalability, start as soon as you realize that it needs to be done. If your target customers aren’t educated enough to realize why they need your product, start investing in a series of educational content pieces of different forms to get them there. If you need to cut the marketing and sales deadweight, do so ASAP. The longer you wait, the more it hurts you and them. Doing it early allows you to give them a fair notice period and time to help them find a more suitable role.
02. Chop the Dead Wood — especially in Management & the C-Suite
Refocus the dollars on the developers, content creators, and solution-focussed sales people who are actually generating value. the doctor can’t say this enough. You wouldn’t believe how many startups in tech have been dragged into oblivion by an overweighted inappropriate management team (because the investors thought big names would bring success) — but if they aren’t the right people for the job, or the job isn’t even needed to begin with, nothing could be further from the truth … and instead of being the buoyant striders intended to get you across the lake, they are the cement shoes that sink you to the bottom.
03. Tell the Truth, No Matter What
Especially around what your product does today, and especially especially with respect to anything asked by a customer. Any individual with a half a brain knows that no product does everything, and any individual with a brain can be educated as to why no product should and, more importantly, why they don’t want some of the features the Free RFP vendors are promoting (because it’s not feature, it’s function, and, more specifically, the function they need to do).
The reality is that a good customer will value the truth, especially when they hear so little of it these days among the lies, damn lies, statistics, Gen-AI, marketing buzzwords and hogwash. Moreover, they know they probably don’t need everything they ask for and definitely not day one (as it takes time to learn modules and suites and use them to full effect). They also know that most of the “wish list” gathered from across the organization is just stakeholders trying to be useful and they really only want the functionality to do their daily jobs, and, more importantly, the stakeholders will be happy if that core functionality is done well.
So if you’re missing a few things, that’s okay. The customers know there will always be pain (if work was always fun, people would want to work for as little as they could afford to), so as long as you can relieve the majority of, and the most common, pain, those customers will be quite happy to suffer a little aggravation here and there instead of the cluster(f6ck) migraine they currently have on a daily basis.
04. Sales Channel Reconsideration
Look at how you are selling now and think about if that is how, or the only way, you should be selling.
If you are not doing partner/channel sales, maybe you need to do partner/channel sales. If there is a niche consultancy advising clients on a daily basis with problems that your solution solves, maybe you should be training those consultants on how your solution can be used to solve the problems, training those consultants on how to install the solution, and then putting a partnership agreement in place for those consultants to sell the solution for you to their clients for which it is appropriate.
If you are relying mostly on partner/channel sales, and they aren’t coming in fast and furious like you hoped, maybe you need to step up direct sales. In the right circumstances the right partners will do wonders for sales, but if they are consultancies, it will be highly dependent on what customers come to them, since most niche consultancies still have to take what they can get (while the Big X take the lion’s share of projects, even those which they probably shouldn’t because they are already so busy trying to support so many clients with digital transformation projects, because any consultant who turns away any work at a Big X risks getting fired). So even if your consulting/services partner is your greatest champion, you can’t always rely on them to be a consistent source of sales.
05. Rethink Partnerships
Regardless if it is part of your strategy or not and what partners you do, or don’t, have today. It’s rare for a company to get it right out of the gate, or for the strategy that is right out of the gate to be the best one down the road as markets change, directions change, plans change, etc. If things are going well, you follow the if it ain’t broke, don’t fix it. If things aren’t going well, you evaluate and rethink it. Your strategy/partners could still be the right strategy/partners, and it just needs more time for the strategy/relationships to take off, or it might be that you need a new strategy/relationship.
No consultancies or complementary offerings selling your solution? Why? We’ve mentioned time and time again that no solution is everything to everyone, and there’s always a complementary solution or service that can add value, even if it takes a bit of work to identify it. So if you don’t have a services / implementation partner trained and certified to sell for you, why not? And if you don’t have relationships with one or more complementary solutions with companies with a complementary culture and value, why not? Even if it is only the odd referral, it could help … and if you’re going up against a suite, and your solution is not, it could definitely help. (After all, most customers who need a “suite” really only need a few key modules, at least for the first few years.)
Alternatively, if you only have partners who filled your ears with sweet nothings until you agreed to be a partner and then gave you sweet nothing once the deal was inked, they are NOT partners, especially if right after the deal was inked they decided to partner with another solution provider with a bigger offering and price tag and sell that instead. Those partners should be dropped faster than a radioactive potato and replaced with a new one.
Stay tuned for Part 2!