Category Archives: rants

Top 10 words or phrases to ban from an RFP response, Part 1

In this two-part article we are going to give you the top 10 words or phrases you should ban from RFP responses if you want a meaningful response to your technology / technology-backed / technology assisted RFP that’s not full of meaningless buzzwords, ambiguity, misdirection, or some combination thereof. The simple fact of the matter is that if you allow any of these phrases, you are not getting an answer, or at least not an answer you need.

10. Savings

Let’s get straight to the point. “Savings” do not exist. Cost avoidance does exist, but if a sourcing event identifies “savings”, it doesn’t mean that you negotiated savings, it meant that you were overspending and that the event identified that overspend so you could make changes to your Procurement to prevent that overspend. That’s it. Savings is money the business accumulates over time. The other definition is finding a way to truly reduce the amount of time, material, or resources to make something — which is something that is up to your supplier to figure out, not you. Your job is to buy at the lowest cost + margin the vendor/service provider will sell for and avoid overspend. The only “savings” you can realize is in the amount of time a process takes (which is why you buy appropriate software platforms to minimize your effort) or the amount of resources a product takes (with a better design). That’s true savings.

9. Market Intelligence

This one absolutely drives the doctor crazy and it should drive you crazy too. WTF is “market intelligence”. The market is not intelligent. In fact, ever since the introduction of Reaganomics, predicated on the false belief that a rising tide floats all boats (as discussed in Why America Abandoned the Greatest Economy in History), one could argue that the market has become decidedly unintelligent (at the same time that American IQ’s have dropped as per a recent article on The Hill, which, of course, we all blame on X).

Now, they may promise better insight into market pricing (but what is that, especially if you can just buy a real-time data feed to commodity indices or public sector contract prices), market dynamics (but isn’t that just buy and sell data), inflation or cost changes (but that requires good predictive analytics, do they have that technology and do they know how to use it), and so on, but only true experts can really provide insight that is likely to come true. And do they have those experts? And what’s their historical accuracy? Most firms don’t have leading experts in the top 10%. Basic math says only 1 / 10 “experts” are in the top 10% and only 1 / 10 companies offering a “market intelligence” service are in the top 10. So ask exactly what information/advice they provide you, how they provide it, how often they update it, who in particular does any manual predictions, and so on.

8. Diversity

Diversity is important. It’s very important. It’s absolutely necessary if you need a supplier to come up with innovative solutions to a problem. But simply allowing a supplier to say they are diverse or check a “diversity” box doesn’t tell you anything. First of all, what’s their definition of diverse. One white woman on a board that otherwise is entirely composed of greedy old white men? Might make their definition of diverse, but definitely, definitely, definitely wouldn’t make the doctor‘s definition of diversity.

True diversity is men and women of all ethnicities, experiential backgrounds, educational backgrounds, and so on that are available to you in the areas in which you employ people. Especially those from diverse backgrounds divergent from your founders / management. And it’s not an arbitrary target, it’s representative of the average diversity in your area. As we have said before, saying you want 50% women in an IT or Engineering company when only 25% of graduates are women is not achievable (but 25% is).

7. Green Procurement

What does “green procurement” mean. the doctor bets you have a definition. And the doctor bets its probably bull crap. Not to say that your intentions, or goals, are bad, or that what you think it is is bad, but that how a less than scrupulous supplier will respond to it is bad. Because when it comes to “green”, there is an awful lot of “greenwashing”, “greenlighting”, “greenrinsing”, “greenhushing”, “greenshifting”, “greencrowding”, or other decidely ungreen practices out there, and if you’re not careful, a supplier will sell you one of these not-so-green services when you ask for a “green” solution. (And, in fact, you’d be greener if you simply asked Kermit the Frog to buy you some lettuce from the local farm. After all, no one knows better than Kermit that It’s Not Easy Being Green.)

6. Sustainable Procurement

What does this mean? It’s even more ambiguous than “green procurement”. Does it mean that what you are buying is sustainable, or does it mean that the process is sustainable. Technically, under the rules of English Grammar (you know, that system of language rules they don’t seem to teach anymore), “sustainable” is an adjective to the “procurement” noun that follows, so as long as the vendor/service provider supports your Procurement process in a way that is sustainable to you, they’ve technically met the requirement, right? Right! But what you want is sustainable goods and services, but that’s not technically what you asked and the sneaky slippery suppliers will try to use that ambiguity to give an ambiguous response and slip a bid in that you shouldn’t consider. So again, don’t ask if they have sustainable procurement, ask what efforts they make to use renewables, minimize resource (water, energy, non-renewable material) use, ensure their suppliers are using sustainable practices and financially sound, and so on.

In other words, buzzwords are not answers, and any provider that simply spews slang at you is not solving serious situations that are relevant to your business. So ban the buzzwords, get deep insight, and make the right decisions.

Of course, since we started at 10, these aren’t the worst of the buzzwords. Not the worst by far! In our next part, we’ll review the top 5. Stay tuned.

Ten Best Practices for (Software) Vendors, Part 6: Bonus Best Practice #3

If you need to catch up:

  • Part 1 Best Practices #1 to #3
  • Part 2 Best Practices #4 to #7
  • Part 3 Best Practices #8 to #10
  • Part 4 Bonus Best Practice #1
  • Part 5 Bonus Best Practice #2

This summer, during the dog days of summer, as a cure to the summertime blues, the doctor gave you ten best practices for success inspired by the common mistakes that the doctor has seen small/mid-sized vendors do over, and over, and over again for the past twenty years (and, more specifically, mistakes that are costing them deeply). And while the best practices linked above won’t necessarily solve all your problems, implementing all of them should prevent a number of major problems, or at least a number of the major problems that are common to multiple technology companies trying to developer and deliver deviceful delicacies to software shoppers.

We stopped at ten, and two significant bonus, tips because ten is the number talent likes to start with, and most of the other issues the doctor has seen repeatedly (that the tips were designed to address) were either a) less relevant or b) less common or occurred less often. However, every time we enter either an extended recession, or a tech downturn (symbolized by the top employers shedding tens of thousands of workers based on economic expectations and fear and not reality [despite bank accounts richer than some nations]), there is one mistake the doctor sees over and over again. Furthermore, this ONE mistake is very dangerous as it prevents some companies from fully recovering, and sometimes starts the downward fall to insolvency or forced (fire)sale to stay in business. To counter it, we give you Bonus Best Practice #3:

BUILD(UP) DURING A DOWNTURN

The biggest mistake the doctor sees over, and over, and over again during a downturn is pushing off (market) research, development, marketing, hires, and other activities necessary for growth until “sales pick up”. The problem is, in many of these smaller enterprises, they usually barely have the resources to support the current customer base and when “sales pick up”, there’s often not even enough manpower for the implementations, so development is stopped to redeploy developers to implementation in the short term; marketing is stopped as those resources are diverted to partnership development with consultancies and implementers; pre-sales support is diverted to account management; and so on. At the same time, the big companies — who can offer bigger salaries, hire faster, and bring more people on board — are planning for rapid hiring, marketing increases, and accelerated development as soon as the market starts to swing up again. They may not be hiring more, spending more on marketing, or augmenting the dev team, but as they have enough resources already, they are preparing to do this. As a result, when the market starts to ramp up, they’re ready to go full swing, be everywhere, demonstrate they are working on a new-and-improved roadmap, and address the major market concerns.

In order to grow as a small/mid-size operation, you need to fully capitalize on up-swings, and the only way to do that is to:

  • have marketing plans and content in place
  • have (pre-)sale position descriptions ready to go and outlets identified
  • have optimized implementation processes in place (so you can do more with less)
  • have partner training courses and support ready to go (so you can augment when you need to)
  • have identified the most critical features that companies want that you don’t have
  • have identified the most innovative/unique/valuable improvements you can start working on and sell as part of the roadmap
  • have done your market research so you can go head-to-head with the big boys who will be ready (and win without properly prepared competition)
  • and so on

AND THIS NEEDS TO BE DONE DURING THE DOWNTURN!

When the upswing starts, it’s too late. Even experienced experts can’t always move fast enough when your more forward thinking peers have been working on their plans in the background since the downswing started and are ready to hit the market full force, while you’re struggling to figure out what to do now that companies are spending again.

Now, the doctor understands that hiring can be an issue because you don’t know precisely when the upswing is going to begin, and if it only takes 3 months of work to get the marketing plan, content, and pre-sales artifacts in place, you don’t want to hire that person 6 months before the upswing. Or maybe it only takes 3 weeks to identify the right improvements to the platform to optimize the implementation process, and then your developers just need to do it. Maybe you only need partner support for training and services with an optimized implementation process, and that’s just completing put-off documentation which only takes a few months (until more platform capabilities are developed). And you don’t have to code features your customer base won’t be ready to use for another two years that take six months to build for another eighteen months, but you do have to know what they are, how long they will take, and how you will sell them. So timing is difficult.

But nowhere did the doctor say you had to hire! Just that you needed to prepare. And, as per Bonus Best Practice #1, Get the Help You Need, you can always hire a contractor or a consultant to get this done, and then, when the upswing starts, sales start coming in, and the marketing, research, product roadmap/management, (pre-)sales, and partner support needs become more intensive, then hire full-time on staff people once the workload for a specific function becomes almost full time.

In other words, the key to success is to get ready to get ‘er done, and get ready to get ‘er done NOW!

The Big X are Pushing Operate Services … But Can They Really Offer Them? And Are They Real?

And if they are real, can anyone?

Backing up, in the beginning, there was traditional Business Process Outsourcing (BPO), which became very common in the 1980s and 1990s as the result of constant claims by the big consultancies and their ilk that the only way businesses could enhance their flexibility and agility and maximize their competitive advantage was to outsource processes they weren’t good at to the Big X Outsourcing offices. (In some cases they weren’t wrong. When the business had no competence in a function, grossly overpaying someone with reasonable competence, even if that someone was not the expert the Big X claimed, generated a good return for the business. The function was done efficiently and effectively, negating the loss the business used to suffer, and it allowed the business to focus on the functions they did well, which increased their profit even as they (often unnecessarily) forked out seven (7) and eight (8) figures to the Big X every year. (And we say unnecessarily because most of the time they could have outsourced to a smaller, niche consultancy at one third to one half of the cost and achieved the same result.)

Then, as Big X tried to steal business from their competitors and niche firms tried to break in, they upgraded to “Managed Services” which was supposed to be more than just performing the service for you cost efficiently (by supposedly reducing your costs by doing it better, and thus, cheaper) and adding value. The idea was that it didn’t just take over a point-based function, but instead provided a dedicated team that basically took over an entire department for you, just offsite, and worked exclusively on your projects. They learned your business, and improved the service offering over time to not only maximize efficiency, but maximize value. If they took over your IT department, they learned the systems you used, optimized those, learned to provide quick and effective problem resolution on the help desk, and, when you needed a new solution, helped you identify the one that would work best with the systems you had. If they took over your AP, they learned your suppliers, your payment rules, your PO formats, and implemented systems that allowed them to match POs to invoices for high-value invoices to reduce overspend. They also helped you build catalogs from suppliers that could meet your MRO / internal needs at the lowest possible cost. And so on. Over time, they not only met SLAs, but improved on all key metrics.

But now a few of the Big X are saying that Managed Services is not enough to maximize value and you need premium “Operate Services” (which come at a premium price, of course). So what’s the difference? Hard to tell. The best definition we can find is it’s a “holistic approach that is focused on delivering outcomes and spurring innovation in a model that leverages automation and data insight to generate substantial business value”. the doctor thought that was what managed services was supposed to do for you? Other definitions indicate that “operate services” differentiate by providing “on demand access to expert talent”. Isn’t that why you use a managed service, so they can identify when the team needs a new expert and add that expert? Other definitions also indicate that “operate services” are more “collaborative”. Are they saying that the managed services they provided to you in the past, where they often acted as an entire department, weren’t collaborative? WTF?

In other words, while they are presenting it as a more advanced premium service model, for which they want to charge you a premium, it really isn’t, or shouldn’t be, because if it is, they are admitting they have been ripping you off for decades!

In some consultancies, it is just a specialization of managed services for IT/IT Security, Analytics-Heavy Functions like Strategic Procurement or Network Analysis, or highly technical functions like supplier identification in direct manufacturing. And it costs more because those people, who are much rarer than experts in traditional business functions and processes, are more expensive, as are the tools that they need to secure your enterprise, analyze your global spend, analyze your supply network, or analyze potential suppliers for your electronic components. And we can see how that could be fair, as long as they aren’t using “operate services” to increase costs across the board where there is absolutely no justification for it.  (And only using it to differing a subclass of specialized services they offer, and admitting its nothing more than managed services, just applied to a new set of business functions.)

But if the consultancy is trying to pitch these “Operate Services” across the board with claims that these new services are better and more specialized for your business than any other kind of service, then they are admitting they are currently ripping you off in your managed services and you should just fire them. Because there should be no difference with the exception that the subclass of operate services we defined in the last paragraph generally require more advanced systems and more resources with a high TQ, which usually cost more. But that’s it.

So don’t blindly fall for this brand new business pitch if they try to pull it on you — simply compare what they are offering to any other firm that says they can fully meet your needs with a traditional managed services model and give the business to the firm that is the most honest among those that can meet your needs.  Now, it might be new and more in depth and more valuable, but that’s not guaranteed.

PostScript: We do believe Big X can offer a lot of value.  See this post on When You Should Use a Big X!

The first jobs lost to OpenAI were at OpenAI? I LOVE IT!

In honour of the first five jobs that were lost to OpenAI, at Open AI (where it was announced the CEO, president, and 3 senior staff were stepping down and/or let go this week).

To the tune of I Love It by Icona Pop (feat. Charli XCX)!

I got this feeling on the winter day when you were gone
You crashed your car into the bridge
I watched, you let it burn
You threw our shit into a bag and pushed it down the stairs
You crashed your car into the bridge

I don’t care, I love it
I don’t care

I got this feeling on the winter day when you were gone
You crashed your car into the bridge
I watched, you let it burn
You threw our shit into a bag and pushed it down the stairs
You crashed your car into the bridge

I don’t care, I love it
I don’t care

I’m on an Earthern road, you’re in the Milky Way
You want me down on earth, but you’re up in space
You’re so damn hard to find, that AI took over
You said it’d take our jobs, but it f*ck3d you over!

I love it
I love it

9% of Companies Claim To Be Ready to Managed Risks Posed by AI? Bull Crap.

the doctor could not believe the recent headline in Forbes that said Only 9% of surveyed companies are ready to manage risks posed by AI. Because there is no way that 9% of companies are ready to manage the risks posed by AI. There’s no way even 0.9% of companies are ready to manage the risks posed by AI.

Why? Because of the rampant introduction of massive LLMs and DNNs that no one understands, for which I’m sure we’ve yet to seen the last of the abysmal failures, hallucinations, and suicide coaxing. There’s simply no way we can even begin to predict all of the potential errors they are going to make, the risks they are putting us under, the repercussions if those errors are made and risks materialize, and how the risks can be minimized, if not mitigated. No way whatsoever.

Not only is it theoretically impossible to be fully prepared, but when you consider that the average organization is not even equipped to handle regular software failures, how can the average organization expect to handle a software-based AI failure it can’t even predict?

The article, which quoted a recent study by RisKonnect (who are obviously able to detect and protect against most types of risk by using RisKonnect, and maybe that’s why they are so confident they can protect and defend against AI risks, but RisKonnect is for traditional enterprise and third-party risk, not cyber risk, and definitely not AI risk — no one can protect against a risk when they don’t even know what the risk is), did quote some very useful statistics on areas of concern. Specifically, of the companies surveyed

  • 65% are concerned about data and cyber,
  • 60% are worried about employees making decisions on erroneous information,
  • 55% are worried about employee misuse and ethical risk,
  • 34% are worried about copyright and intellectual property, and
  • 17% are worried about discrimination risk.

The risks are the right risks, and the order of priority is about the right order, but the percentage of companies concerned is much too low.

1. 100% of companies should be concerned about data and cyber. Not only are we in the age of state-sponsored hacking, which makes any company with useful confidential designs and information a target, but with almost all significant commerce being conducted online, all companies are a target for financial fraud.

2. 100% of companies that need to make decisions based on data analysis should be concerned about erroneous information, as all companies have bad data, and the bigger the company, the worse the data.

But none of these match the risks of AI. As per the quote in the article from Caitlin Begg, an over-reliance on AI can risk robotic, insensitive, spammy, or off-topic messaging, and that’s just the beginning. As noted, most companies haven’t simulated their worst case scenario, and since one can’t even predict what that is with AI, they aren’t even close to ready. It’s not just another article in the organization’s tech stack, even though the article seemed to indicate it is. One can prioritize transparency, accountability, threat and vulnerability monitoring, and risk mitigation, but when most AI applications can’t explain their actions, aren’t accountable humans, have no realistic threat and risk assessments, and there is no way to mitigate risk except not to use the technology in the first place for any decision that should be made by a HUMAN, it’s just not enough.

The precautionary steps are not to identify where AI can be most effective and incorporate it, the steps should be to

  1. identify where partners and third parties are using AI and putting your organization at risk
  2. identify where employees might be using unapproved web-based AI applications and put a stop to it
  3. identify where your SaaS providers are not only using, but introducing, AI into their applications after purchase and delivery and ensure that any utilization is bounded, tested, and properly constrained to prevent risk

Then, instead of unbounded AI, identify appropriate automation technologies that can be properly configured, integrated, and managed as part of an enterprise stack. And reap the rewards while your competitors deal with risks.