Category Archives: rants

Reporting is Not Analysis — And Neither Are Spreadsheets, Databases, OLAP Solutions, or “Business Intelligence” Solutions

… and one of the best explanations the doctor has ever read on this topic (which he has been writing about for over two decades) was just published over on the Spendata blog on Closing the Analysis Gap. Written by the original old grey beard himself (who arguably built what was the first stand alone spend analysis application back in 2000 and then redefined what spend analysis was not once, but twice, in two subsequent start-ups that built two, entirely new, analytics applications that took a completely different, more in-depth approach), it’s one of the first articles to explain why every current general purpose solution that you’re currently using to try and do analysis actually doesn’t do true analysis and why you need a purpose built analysis solution if you really want to find results, and in our world, do some Spend Rappin’.

We’re not going to repeat the linked article in its entirety, so we’ll pause for you to go read it …

 

… we said, go to the linked article and read it … we’ll wait …

 

READ IT! Then come back. Here’s the the linked article again …

 

Thank you for reading it. Now we’ll continue.

As summarized by the article, we have the following issues:

Tool Issue Resolution Loss of Function
Spreadsheet Data limit; lack of controls/auditability Database No dependency maintenance; no hope of building responsive models
Database performance on transactional data (even with expert optimization) OLAP Database Data changes are offline only & tedious, what-if analysis is non-viable
OLAP Database Interfaces, like SQL, are inadequate BI Application Schema freezes to support existing dashboards; database read only
BI Application Read only data and limited interface functionality Spreadsheets Loss of friendly user interfaces and data controls/auditability

In other words, the cycle of development from stone-age spreadsheets to modern BI tools, which was supposed to take us from simple calculation capability to true mathematical analysis in the space age using the full breadth of mathematical techniques at our disposal (both built-in and through linkages to external libraries), has instead taken us back to the beginning to begin the cycle anew, while trying to devour itself like an Ouroboros.

Why did this happen? The usual reasons. Partly because some of the developers couldn’t see a resolution to the issues when they were first developing these solutions, or at least a resolution that could be implemented in a reasonable timeframe, partly (and sometimes mostly) because vendors were trying to rush a solution to market (to take your money), and partly (and sometimes largely) because the marketers keep hammering the message that what they have is the only solution you need until all the analysts, authors, and columnists repeat the same message to the point they believe it. (Even though the users keep pounding their heads against the keyboard when given a complex analysis assignment they just can’t do … without handing it off to the development team to write custom code, or cutting corners, or making assumptions, or whatever.) [This could be an entire rant on its own how the rush to MVP and marketing mania sometimes causes more ruin than salvation, but considering volumes still have to be written on the dangers of dunce AI, we’ll have to let this one go.]

The good news is that we now have a solution you can use to do real analysis, and this is much more important than you think. The reality is that if you can’t get to the root cause of why a number is as it is, it’s not analysis. It’s just a report. And I don’t care if you can drill down to the raw transactions that the analysis was derived from, that’s not the root cause, that’s just supporting data.

For example, profit went down because warranty costs increased 5% is not helpful. Why did warranty costs go up? Just being able to trace down to the transactions where you see 60% of that increase is associated with products produced by Substitional Supplier is not enough (and in most modern analysis/BI tools, that’s all you can do). Why? Because that’s not analysis.

Warranty costs increasing 5% is the inevitable result of something that happened. But what happened? If all you have is payables data, you need to dive into the warranty claim records to see what happened. That means you need to pull in the claim records, and then pull out the products and original customer order numbers and look for any commonalities or trends in that data. Maybe after pulling all this data in you see, of the 20 products you are offering (where each would account for 5% of the claims if all things were equal) there are 2 products that account for 50% of the claims. Now you have a root cause of the warranty spend increase, but not yet a root cause of what happened, or how to do anything about it.

To figure that out, you need to pull in the customer order records and the original purchase order records and link the product sent to the customer with a particular purchase order. When you do this, and find out that 80% of those claims relate to products purchased on the last six monthly purchase orders, you know the products that are the problem. You also know that something happened six months or so ago that caused those products to be more defective.

Let’s say both of these products are web-enabled remote switch control boxes that your manufacturing clients use to remotely turn on-and-off various parts of their power and control systems (for lighting, security monitoring, etc.) and you also have access, in the PLM system, to the design, bill of materials (BOM), and tier 2 suppliers and know a change takes 30 to 60 days to take effect. So you query the tier 1 BOM from 6, 7, 8, and 9 months ago and discover that 8 months ago the tier 2 supplier for the logic board changed (and nothing else) for both of these units. Now you are close to the root cause and know it is associated with the switch in component and/or supplier.

At this point you’re not sure if the logic board is defective, the tier 1 supplier is not integrating it properly, or the specs aren’t up to snuff, but as you have figured out this was the only change, you know you are close to the root cause. Now you can dive in deep to figure out the exact issue, and work with the engineering team to see if it can be addressed.

You continue with your analysis of all available data across the systems, and after diving in, you see that, despite the contract requiring that any changes be signed off by the local engineering team only after they do their own independent analysis to verify the product meets the specs and all quality requirements, you see that the engineering, who signed off on the specs, did not sign off on the quality tests which were not submitted. You can then place a hold on all future orders for the product, get on the phone with the tier 1 supplier and insist they expedite 10 units of the logic board air freight for quality testing, and get on the phone with engineering to make sure they independently test the logic boards as soon as they arrive.

Then, when the product, which is designed for 12V power inputs, arrives and the engineers do their stress tests and discover that the logic board, which was spec’ed to be able to handle voltage spikes to 15V (because some clients power backup systems off of battery backups that run off of chained automotive batteries) actually burns out at 14V, you have your root cause. You can then force the tier 1 supplier to go back to the original board from the original supplier, or find a new board from the current supplier that meets the spec … and solve the problem. [And while it’s true you can’t assume that all of the failure increases were the logic board without examining each and every unit of each and every claim, in this situation, statistically, most of the increase in failures will be due to this [as it was the only change].]

In other words, true analysis means being able to drill into raw data, bring in any and all associated data, do analysis and summaries of that data, drill in, bring in related data, and repeat until you find something you can tie to a real world event that led to something that had a material impact on the metrics that are relevant to your business. Anything less is NOT analysis.

“Generative AI” or “CHATGPT Automation” is Not the Solution to your Source to Pay or Supply Chain Situation! Don’t Be Fooled. Be Insulted!

If you’ve been following along, you probably know that what pushed the doctor over the edge and forced him back to the keyboard sooner than he expected was all of the Artificial Indirection, Artificial Idiocy & Automated Incompetence that has been multiplying faster than Fibonacci’s rabbits in vendor press releases, marketing advertisements, capability claims, and even core product features on the vendor websites.

Generative AI and CHATGPT top the list of Artificial Indirection because these are algorithms that may, or may not, be useful with respect to anything the buyer will be using the solution for. Why?

Generative AI is simply a fancy term for using (deep) neural networks to identify patterns and structures within data to generate new, and supposedly original, content by pseudo-randomly producing content that is mathematically, or statistically, a close “match” to the input content. To be more precise, there are two (deep) neural networks at play — one that is configured to output content that is believed to be similar to the input content and a second network that is configured to simply determine the degree of similarity to the input content. And, depending on the application, there may be a post-processor algorithm that takes the output and tweaks it as minimal as possible to make sure it conforms to certain rules, as well as a pre-processor that formats or fingerprints the input for feeding into the generator network.

In other words, you feed it a set of musical compositions in a well-defined, preferably narrow, genre and the software will discern general melodies, harmonies, rhythms, beats, timbres, tempos, and transitions and then it will generate a composition using those melodies, harmonies, rhythms, beats, timbres, tempos, transitions and pseudo-randomization that, theoretically, could have been composed by someone who composes that type of music.

Or, you feed it a set of stories in a genre that follow the same 12-stage heroic story arc, and it will generate a similar story (given a wider database of names, places, objects, and worlds). And, if you take it into our realm, you feed it a set of contracts similar to the one you want for the category you just awarded and it will generate a usable contract for you. It Might Happen. Yaah. And monkeys might fly out of my butt!

CHATGPT is a very large multi-modal model that uses deep learning that accepts image and text as inputs and produces outputs expected to be inline with what the top 10% of experts would produce in the categories it is trained for. Deep learning is just another word for a multi-level neural network with massive interconnection between the nodes in connecting layers. (In other words, a traditional neural network may only have 3 levels for processing with nodes only connected to 2 or 3 nearest neighbours on the next level while a deep learning network will have connections to more near neighbors and at least one more level [for initial feature extraction] than a traditional neural network that would have been used in the past.)

How large? Large enough to support approximately 100 Trillion parameters. Large enough to be incomprehensible in size. But not in capability, no matter how good its advocates proclaim it to be. Yes, it can theoretically support as many parameters as the human brain has synapses, but it’s still computing its answers using very simplistic algorithms and learned probabilities, neither of which may be right (in addition to a lack of understanding as to whether or not the inputs we are providing are the right ones). And yes it’s language comprehension is better as the new models realize that what comes after a keyword can be as important, or more, than what came before (as not all grammars, slang, or tones are equal), but the probability of even a ridiculously large algorithm interpreting meaning (without tone, inflection, look, and other no verbal cues when someone is being sarcastic, witty, or argumentative, for example) is still considerably less than a human.

It’s supposed to be able to provide you an answer to any query for which an answer can be provided, but can it? Well, if it interprets your question properly and the answer exists, or a close enough answer exists and enough rules for altering that answer to the answer that you need exists, then yes. Otherwise, no. And yes, over time, it can get better and better … until it screws up entirely and when you don’t know the answer to begin with, how will you know the 5 times in a hundred it’s wrong and which one of those 5 times its so wrong that if you act on it, you are putting yourself, or your organization, in great jeopardy?

And its now being touted as the natural language assistant that can not only answer all your questions on organizational operations and performance but even give you guidance on future planning. I’d have to say … a sphincter says what?

Now, I’m not saying properly applied these Augmented Intelligence tools aren’t useful. They are. And I’m not saying they can’t greatly increase your efficiency. They can. Or that appropriately selected ML/PA techniques can’t improve your automation. They most certainly can.

What I am saying are these are NOT the magic beans the marketers say they are, NOT the giant beanstalk gateway to the sky castle, and definitely NOT the goose that lays the golden egg!

And, to be honest, the emphasis on this pablum, probabilistic, and purposeless third party tech is not only foolish (because a vendor should be selling their solid, specialty built, solution for your supply chain situation) but insulting. By putting this first and foremost in their marketing they’re not only saying they are not smart enough to design a good solution using expert understanding of the problem and an appropriate technological solution but that they think you are stupid enough to fall for their marketing and buy their solution anyway!

Versus just using the tech where it fits, and making sure it’s ONLY used where it fits. For example, how Zivio is using #ChatGPT to draft a statement of work only after gathering all the required information and similar Statements of Work to feed into #ChatGPT, and then it makes the user review, and edit as necessary, knowing that while the #ChatGPT solution can generate something close with enough information and enough to work with, every project is different and an algorithm never has all the data and what is therefore produced will never be perfect. (Sometimes close enough that you can circulate it is a draft, or even post it for a general purpose support role, but not for any need that is highly specific, which is usually the type of need an organization goes to market for.)

Another example would be using #ChatGPT as your Natural Language Interface to provide answers on performance, projects, past behaviour, best practices, expert suggestions, etc. instead of having the users go through 4+ levels of menus, designing complex reports/views and multiple filters, etc. … but building in logic to detect when a user is asking a question on data versus asking for a prediction on data vs. asking for a decision instead of making one themself … and NOT providing an answer to the last one, or at least not a direct answer. For example, how many units of our xTab did we sell last year is a question on data the platform should serve up quickly. How many units do we forecast to sell in the next 12 months is a question on prediction the platform should be able to derive an answer for using all the data available and the most appropriate forecasting model for the category, product, and current market conditions. How many units should I order is asking the tool to make a decision for the human so either the tool should detect it is being asked to make a decision where it doesn’t have the intelligence or perfect information to do and respond with I’m not programmed to make business decisions or return an answer that the current forecast for the next quarter’s demand for xTab for which we will need stock is 200K units, typically delivery times are 78 days, and based on this, the practice is to order one quarter’s units at a time. The buyer may not question the software and blindly place the order, but the buyer still has to make the decision to do that.

And no third party AI is going to blindly come up with the best recommendation as it has to know the category specifics, what forecasting algorithms are generally used, why, the typical delivery times, the organization’s preferred inventory levels and safety stock, and the best practices the organization should be employing.

AI is simply a tool that provides you with a possible (and often probable, but never certain) answer when you haven’t yet figured out a better one, and no AI model will ever beat the best human designed algorithm on the best data set for that algorithm.

At the end of the day, all these AI algorithms are doing is learning a) how to classify the data and then b) what the best model is to use on that data. This is why the best forecasting algorithms are still the classical ones developed 50 years ago, as all the best techniques do is get better and better and selecting the data for those algorithms and tuning the parameters of the classical model, and why a well designed, deterministic, algorithm by an intelligent human can always beat an ill designed one by an AI. (Although, with the sheer power of today’s machines, we may soon reach the point where we reverse engineer what the AI did to create that best algorithm versus spending years of research going down the wrong paths when massive, dumb, computation can do all that grunt work for us and get us close to the right answer faster).

For all I care, they can ban all the Social Media Platforms!

For those who haven’t heard, Montana is the first state to try and ban TikTok, presumably because it’s owned by China that is harvesting the data. Following that logic, shouldn’t they ban every platform that has Chinese investment?

… and then every social media platform that has a presence in China and, as such, must adhere to Chinese law?

Of course, if the real reason they want to ban Social Media platforms is because they realize the damage that social media platforms have been doing to us (and are using the Chinese ownership as an excuse), they can ban them all — including their home-grown American platforms. After all, Twitter made us dumber than a doornail and Facebook is a Toilet so please feel free to take them away too.

Remember, even if you overlook the fact that Facebook is primarily used for sharing conspiracy theories and information that is NOT fact-checked, seeking attention, cyber-stalking your favourite celebrities, and other uses besides the good, wholesome, community aspects they tirelessly promote, if you acted in real life like you acted on Facebook, as the image below suggests, you’d be the subject of multiple psychological assessments and suspicious individual #1 at your local precinct. (Credit to the original source, which I wish I knew!)

Don’t Cheat Yourself with Cheat Sheets, Kid Yourself with KPI Quick Lists, or Rip Yourself Off with Bad RFPs!

In an effort to quickly catch up on the parts of S2P the doctor hasn’t been covering as much in the past few years, when he was focussed primarily on Analytics, Optimization, Modelling, and advanced tech in S2P (inc. RPI, ML, “AI”, etc.), he’s been paying more attention to LinkedIn. Probably too much, even though he can (speed) read very fast and skim a semi-infinite scroll page in a minute. Why? Because a lot of what he’s been seeing is troubling him, and as per last Friday’s post, sometimes angering him when predatory sales-people and consultants are giving other sales-people and consultants bad advice (presumably to increase their follower count or coaching sales or whatever) that will not only hurt what could be a well-intentioned sales-person or consultant (they still exist, though sometimes it seems they are fewer by the year as more sales people bleed into our space from enterprise software, looking for the next hot software solution and the next big payday), but also the individuals, and companies, those influenced sales people sell to in the thoughtless, emotionless, uncaring aggressive style the predatory sales coaches are mandating. (Not to say that a sales person shouldn’t be aggressive about getting a sale, just that they should be focussed on the companies they can actually help and be focussed on getting the customer all the information and insight that customer needs to make the right choice, feel comfortable about it, and feel prepared to defend it. The aggression should be channeled into making sure their company does everything it can to properly educate the potential client before that client commits to a long term relationship.)

A few of the things that have been repeatedly troubling him is

  1. all the cheat sheets he’s been seeing for those looking to get a better grip on Procurement and how it integrates into the rest of the business, that supposedly summarize everything you need to know about accounting, finance, payments / accounts payable, etc. to help you make good choices about Procurement in general;
  2. all the 10/20/50 Procurement, Spend, Manufacturing, etc. KPIs that you need to keep tabs on your Procurement, cashflow plan, product lifecycle, etc.; and
  3. all the RFP outlines or guidances that are being made available, sometimes by leaving your email, to help buyers acquire a certain technology.

And it’s not because they’re bad. They’re not. Some of them are actually quite good. A few are even excellent. Some of the cheat sheets and KPI lists the doctor has seen are incredibly well thought out, incredibly clear, and incredibly useful to you. Some are so good that, as a buyer, likely with little support from your organization and even less of a training budget, you should be profusely thanking whomever was so kind to create this for you and give it away for free.

Nor is it because the doctor suspects any ill intent or malice behind the efforts (in the vast majority of the cases). Many of these people giving away the cheat sheets or the KPI lists are generally trying to help their fellow humans get better at the job and improve the profession overall. And when the RFP outline is coming from a former practitioner, it’s also the case that they are typically trying to help you out (and maybe sell their services as a consultant, but they are providing proof of value up-front).

So why has it been troubling the doctor so? It took a while and some thought to put his finger on it, and the answer is, surprisingly, one of the reasons [but not the obvious one] that the doctor hates software vendor RFPs and despises any vendor that gives you one.

Now, the primary reason the doctor despises those RFPs, which became popular when Procuri started doing it en-masse in the mid-to-late 2000s (before being acquired by Ariba and quietly sunsetted as the integration never finished by the time Ariba sold to SAP, for those of you who remember the APE circus), is that these RFIPs are always written to be entirely one sided and ensure the vendor giving them away ALWAYS comes out on top. The feature list is exactly what the vendor offers, the weightings correspond exactly to the vendor core strengths, etc. etc. etc. And don’t tell me you can start with a vendor RFP and alter it to suit other vendors, because you can’t. You’d have to know all the features as the vendor focussed on point features, not integrated functions, and you, as a buyer who’s never used a modern system, have no knowledge of how to equate features (when vendor specific terminology is used), or how to determine if one feature is more advanced than another. (That was the reason the doctor co-developed Solution Map, to help rate and evaluate technology, which is the one thing most buying organizations can’t do well. Not the things they can do well, and better than most analyst firms, like rate the appropriateness of services to them, assess whether or not the vendor has a culture that will be a good fit, define their business needs and goals, etc.)

But the primary reason doesn’t apply here. So what’s the secondary reason? When an average, overworked, underpaid, and overstressed buyer got their hands on one of these free vendor RFPs, especially when the RFP was thick, heavy, and professionally edited and prepared to look polished and ready for use, and was more detailed than what the buyer could do, they thought they had their answer and could run with it. They thought it was all they needed to know, for now, and that they could send it out, collect the responses, and get back to fire-fighting. They were lulled into a false sense of security.

And that’s why these cheat sheets and KPI guides and former buyer/consultant RFPs are so troubling. When you’ve been struggling without even the basics, and these are so good that they teach you all the basics, and more, it seems like they have all the answers you need and that when you learn those basics, encapsulate them in the tool, and start running your business against them, things will be better. Then you configure your tool to respect the basics, encode the KPIs, and things are better. Significantly better, and for once processes start going smoothly. And then you believe you know everything you need to in that area (that’s not your primary area) to interface with those functions and that those KPIs will be enough to keep you on the Procurement track and let you know if there are any issues to be addressed. And you start operating like that’s the case. But it’s not.

And that’s the problem — these cheat sheet, guides, and templates, which are much better than what you’d get in the past, can make such a drastic difference when you first learn and implement them that they instill a false sense of security. You get complacent with your integrations, reports, and KPI monitors, not recognizing that they only capture and catch what they were encoded to capture and catch. However, real world conditions are constantly changing, the supply base is constantly changing, and external events such as natural disasters, political squabbles, and endemics are coming fast and furious. If the risk metric doesn’t take into account external events, real-time slips in OTD (as it is based on risk profiles upon onboarding, and updates upon contract completion), or past regulatory compliance violations (as an indicator of potential violations in the future), the organization could be blindsided by a disruption the buyer thought the KPI would prevent. Similarly, the wrong cash-flow related KPIS can give a false sense of liquidity and financial security and the wrong inventory metrics can lead to the wrong forecasts in outlier categories (very fast moving, very slow moving, or recently promoted).

In other words, by giving you the answers, without the rationale behind them, or deep insight into how appropriate those answers are to your situation, you will cheat yourself, kid yourself, or, even worse, rip yourself off. And that’s worrisome. So please, please, please remember what these are — learning aids and starting points only — not the end result. (Especially if it’s an RFP template.)

Dear Vendor Rep, when you hear “We have trouble … ” You SHOULD NOT assume the individual wants you to sell them whatever your closest solution is. NEVER!

Another Friday. Another dozen topics to rant about. But one has to surface to the top, and this week, it’s the circulating documents and advice on LinkedIn on what a vendor sales rep should say when a potential customer says “X”. I don’t want to get to specific, and inadvertently call people out (although I may if I see a continued push for this nonsense), but needless to say, as this is a Friday, and another rant, the “advice” being given is entirely wrong and total BullSh!t! And I’m sick of it, and as a potential customer, you should be too.

As an example, and this is not necessarily a specific example, I’ve been seeing advice along the lines of:

If a potential customer says “we have trouble managing our inventory and/or raw materials”

Then a vendor rep should hear “our business could be stalled or halted if we don’t have what we need to satisfy our customer demand, produce our products, or run our production lines” and “therefore, I want inventory management, product tracking, and or storeroom/warehouse management software and I want it now“.

And then that vendor rep should identify their most appropriate software solution or platform and say “our Gruntmaster 6000 module is exactly what you are looking for as it tracks your inventory on-hand by quantity and location, as well as in process by lane and supplier, lets you assign it to builds and customers, and gives you an accurate picture of what you have on hand and when you will need to restock and even prompts to re-order” …

H3CK NO! ( Get lost, Phil. )

As another example, if a potential customer says “we are in immediate need of Procurement cost savings”

Then a vendor rep should hear “if we don’t get a cutting edge e-Sourcing or e-Procurement solution ASAP we are going to get fired so, please, find us one, no matter what it costs”

And then that vendor rep should identify their most appropriate software platform and say “our new Ovation Sourcing Suite, running on the new-and-improved Phantom operating system, is exactly what you need as it will save your organization at least 10% annually on your addressable spend, which we estimate to be 400M based on your current spend profile, so you can easily afford the low, low, annual license cost of 4M”

AGAIN, H3CK NO! (Phil, we’re warning you!)

In neither situation does the individual want a sale. They want a solution, but that’s not a sale, and not necessarily even a piece of software.

Specifically, they want to understand what their problem is, why they are having the problem, what processes could be changed to prevent the problem, and only then what a solution needs to be in order to help them (and they want to understand what they need before they are asked to judge a solution, and how valuable that solution really is). At least if they are an individual with independent thought who wants to remain that way. (the doctor does realize that there are apparently quite a few individuals [numbering in the thousands] who would rather just belong to a cult of savings and/or a cult of technology and that there is at least one predatory vendor out there that seeks these customers out and actively convinces them to repeat the “savings” mantra until they buy in and join the cult. But there are still quite a few individuals who may eventually want your technology who abhor cults and want to retain their individuality.)

Thus, when a customer says “we are in immediate need of Procurement cost savings”

What you should say is “we need to do something or our jobs are on the line, but we don’t know what and we need some guidance”

And before you give them a single word of guidance, you should ask, not say, ask “why, what’s your reasoning, and where do you think that savings could come from“.

If the reason is “the boss said if we don’t cut the costs he’ll cut our jobs“,

then you should say “okay, so your boss thinks you are overspending — that may or may not be the case in the current economic and supply chain environment; the first thing you should do is a category-based spend analysis against market benchmarks to identify where your spending is, and whether any savings is likely in each category with significant spend; then, based upon any identified opportunities, you need to determine the best way to capture those savings which could be renegotiating with contracted suppliers (in exchange for a longer term), putting spot-buy suppliers under contracts, or going to market with a (multi-round) RFP”

and only then should you say, “now, if you would like us to help, we offer a spend analysis tool if you can do the analysis yourself and/or [guided] spend analysis services and/or we partner with consultancy CCA who can help you with the analysis; then, if you determine that you need RFP technology, we have an advanced sourcing product that could be a perfect fit, and if you determine (re-)negotations are the big problem, we also have a contract management solution/integration with negotiation support that many of your peers have said works great in those situations; we’ll reach back out in x weeks, which is about how long the initial analysis should take, but if you get answers sooner we’re here to help”

Not only will the potential customer respect you, but you will be their first callback as soon as they know what they need, and if they can skip an open RFP process in their technology selection, it’s likely you will be their first choice because they want a vendor who will listen to them, understand their problems, help them identify the root cause and the necessary processes changes and improvement, and ensure that any solution they buy is one that’s actually appropriate to their situation and one they can use. And this will be true even if your solution costs more because they are looking first and foremost for a vendor that will help them achieve the promised ROI, not just promise them one (or insist they drink the kool-aid). (Please don’t sip the Kool Aid.)

The situation for the inventory example is similar. Almost every manufacturer has an MRP, and knows what they are buying/using, so it’s likely their inventory issue is a process issue, possibly exacerbated by a lack of integration between systems, or a lack of visibility into forthcoming production plans. Similarly, every organization knows what they buy, it’s on the PO, and they know what is shipped, it’s on the ASN, and if they have a no-receipt, no-pay policy, they know they should have received what was in the ASN. But chances are there is no counting, or ASN override, when receipt is verbally acknowledged (and a buyer keys in a single “Y” when the warehouse clerk says “yeah, we got it“), no connection between the procurement system and the inventory system, no identification of where the product is stored, and no indication of whom the product was intended for.

In other-words, they probably don’t need an inventory system, they probably need an integration solution/module that connects the systems, consulting on best practices to help them get the processes right, and auxiliary modules for sales tracking or integration into sales so the inventory is properly allocated.

They may still need your solutions, but they need your knowledge first, and if you offer the right services, possibly need your consulting, more.

Remember this before you take that bad advice to lay right into an inappropriate sales pitch. At least if you want them to want you. (They don’t want a Cheap Trick anymore.)