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Good morning, you're listening to Breakfast Bites and I'm Felicia King.

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Today's show, I'm going to share some wisdom with you from my past 30 years

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of experience in the business world and relate that into something that I talk

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about rather frequently, which is what organizations need to be doing in order to survive and thrive.

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So this is kind of another in my series of trying to help you survive and thrive

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in the changing landscape of challenges that organizations of all shapes and

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sizes and flavors are being presented with. So let's get started.

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I'm going to give you a little background on why what I'm going to tell you

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about is so darned important. Businesses now are faced

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with challenges i think more than

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ever before associated with finding employees who are reliable who are capable

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dependable trustworthy and they are spending entirely too much time businesses

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are spending too much time dealing with the.

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Management of those challenges.

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So a lot of variability and having the right staff available to do the right

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services for customers or to be there to build the right products for customers at the right time.

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So there's a lot of challenges and you see that the, you see a lot of organizations

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doing robotics as a result of it.

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And in the AI era, which is where we're at,

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what is going to happen, I think,

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is that organizations will be decoupling a lot of their business processes from

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being dependent upon organizations.

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Specialty labor and when i say specialty labor

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i mean i'm talking about labor where you wrote

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a job description and someone needed

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to have some skill set to do something as opposed to just

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any old random person off the street being

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able to do something there's some level of specialty skill

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set that they have you know and i'm not talking about using ai to you know eliminate

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human creativity i'm absolutely not using that i'm not saying that whatsoever

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but i am saying that there are some massive problems that employers have,

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regardless of whether it's a nonprofit or a for-profit, doesn't really matter.

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I think most of these organizations have the same problems, at least in my observation.

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And there are foundational pieces that have to be in place in order for them

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to be able to utilize AI effectively.

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One of the things that's happening right now is a lot of organizations lack,

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in fact, I'd argue the vast majority of organizations lack operational maturity,

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which has led them to a situation where they're not ready for AI,

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but yet they haven't made the decision to block it or to even have a policy around it.

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There is a lack of executive management wanting to put constraints and guardrails around things.

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Spending time thinking about protecting the company assets or protecting the

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customer's data is seen by a lot of, especially sales executives.

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As something that isn't helping sales at all.

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And the sales executives in an organization are generally the ones that are

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driving the agenda in an organization,

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unless you're talking about a technologist-driven organization by people who

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were fundamentally engineers from the very beginning, that might be the exception to that.

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So usually organizations are sales driven.

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And so whatever the perceived needs and wants are of sales executives,

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that tends to be what gets the most amount of attention. And it's fairly rare

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for them to be pushed back.

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What I mean by pushback is that they want to use whatever is the cool,

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new, sexy thing that they think is going to help them be competitive.

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And when you're dealing with an organization that lacks a very strong,

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empowered, and supported chief technology officer,

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there is no one in the organization that is pushing back on the adoption of

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dangerous technologies. And I do mean dangerous technologies.

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AI can be exceedingly dangerous. You could have a situation where an employee

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who hasn't been provided a policy about AI use,

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And they're able to access it because it's not getting blocked because,

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you know, some sales executive decided that they needed to have access to it.

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Or you have, you know, some salesperson who's like, you know,

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the world is going to melt down. I can't possibly do my job.

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This is a real thing. I hear this, you know, like they just I can't do my job

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at all unless I have access to chat GPT.

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And I think to myself, what did you do before chat GPT?

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What happened to your use of and command of the english language you know what

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happened to your ability to use spreadsheets you know and word documents what

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what happened with that you know so there's there's some there's some silliness

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obviously that's involved there as well,

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but it's all about that company culture these organizations are rarely rarely

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putting forth a policy around AI and then requiring employees to do training

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so that they know what to do and what not to do with AI.

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Because even the slightest improper use of AI is basically taking company confidential

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data, employee confidential data, customer confidential data,

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trade secrets, you name it, all kinds of things.

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It's taking those things and it's now putting it effectively in the public sphere

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through the use of something like ChatGPT.

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There are no guardrails on AI like that.

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Now, the consensus in the technology space is basically this.

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And let me caveat a little bit further. The technology space of people who I

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think have the credibility to have an opinion that should be considered,

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because obviously there's a lot of horse hockey that gets bantied about.

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So the technologists whose opinions are actually worth listening to have two

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general statements about AI. The first one is that you have to be very concerned about losing your company

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data and increasing massive amounts of risk when you're utilizing an AI that

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you can't control the boundaries on.

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So the use of anything that is like ChatGPT needs to be you're running your own AI instance.

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You're not utilizing a subscription model to something where you upload the data,

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your data, and it now gets combined with the master, basically publicly available data set.

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Okay, so that's literally where your employees are breaching your company through the use of AI.

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And the other thing that the technologists are saying about it is that there's

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really only one company right now that is democratizing AI.

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So when I say democratizing AI, I'm saying that you can actually put secure guardrails around it,

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but it can be utilized for a financially amenable amount of money on a monthly

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basis. or an annual basis. So it's, you can have both components that you need for it to be usable and workable.

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One, you can have the security aspects around it, but you can also then have

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accessibility because it's affordable.

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If you had to rev up your own separatized AI instance, where you had to host

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that yourself on your own server infrastructure and such,

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that is way outside the scope of the wheelhouse of even many organizations that

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have full-time internal IT departments and whose revenue is over 500 million a year in revenue.

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It's all about whether or not you're deeply technology-centered,

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and the vast majority of organizations are not.

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Okay, so how do you put some boundaries and guardrails around the use of AI

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so you can benefit from it without it becoming a risk and breach factor for you.

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Well, you have to control your data. You have to control the bounds of your

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data, who has access to the data, what can be done with that data.

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Well, when you reflect upon that, it becomes very obvious that it's required

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to use technologies like data loss prevention, digital rights management,

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automatic sensitivity labeling, and a whole host of other protective features,

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which are bluntly very difficult to implement and very time-consuming to implement.

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It can be done, but I feel very confident in saying that most likely anyone

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with less technical skill than I have is going to significantly struggle with that.

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And simultaneously, it cannot be simply a one-and-done sort of project that

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a business hires somebody like myself to do for them.

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It's a paradigm shift for the organization.

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And most organizations are not ready for it.

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So I'm going to recap here because I know this is a little complicated.

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If you're going to be ready for AI, if you're going to use AI in your organization,

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whether you're a nonprofit, for-profit, it doesn't matter to me.

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What matters is that you're risk management.

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You're doing good risk management because you have a legal obligation to not take,

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employee data, customer data, and just shove it out there into the internet

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and to the public space, which is effectively what somebody is doing when they

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take that kind of data and they throw it into something like ChatGPT.

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Unless, of course, you're running your own ChatGPT instance,

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which I already said was prohibitive, cost prohibitive.

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And that is not what 99.9% of organizations are doing. They're not running their own AI instance.

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So what becomes the success model? We're talking about data retention policies,

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data classification policies, data sensitivity labels, the technical implementations

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of those, a governance system, people being organized,

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standards must exist, policies must exist.

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And fundamentally, the culture of a company has to change. It has to become

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more operationally mature. And they have to drive towards a culture of seeking to be more efficient,

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more transparent, more operationally mature.

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And ultimately, the result of that is profitability goes up.

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So I was working on a presentation for a business group to teach them about

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why they should be driving cultural change in their organization towards profitability

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and operational maturity. And I reflected upon the fact that, wow, this is all just a prerequisite to being ready for AI.

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So there's a ton of converging reasons why organizations need to do this,

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but I'll give you one more. I encountered an article that was talking about how Generation Z faces a difficult

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labor market due to AI and their own bad habits.

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And in this article, it talks about the bad habits that Generation Z oftentimes has,

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not all, but certainly a significant enough percentage of Generation Z workers

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to the point where it has managed to matriculate to become an article published about it.

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And it's basically talking about how

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it's so difficult for employers to get economic value from those employees to

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the point where there is more pain for them to have that employee than not having that employee.

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So they'd rather deal with the gap of not having somebody to fulfill whatever

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those job functions are versus the pain of having that person there.

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So they're absolutely, in the perspective of those employers,

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they had hired people and then gotten to the point where they realized that

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it's literally costing us way too much money to have these employees.

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Not only were those employees not profitable, they weren't contributing towards

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profitability, but they were also taking the company negative, right?

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They were negatively impacting profitability.

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So it wasn't even a break-even thing. And as a result, they got terminated.

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In an effort for organizations to get to the point where they can become more

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resilient to the impacts of those fluctuations,

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you know, we all would love to find more golden unicorns and they are a far and few between.

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And so there's been this shift towards, well, let's do better training.

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And I think training is absolutely center to these efforts to solving these problems.

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But there's a bigger issue at hand, and the issue at hand is actually operational maturity.

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So the organization simultaneously has to become more operationally mature,

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but they have to drive all of the staff behavior to align with those things.

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So I'm talking about policies, standards, processes.

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Intentional resiliency, intentional business continuity,

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intentional actions towards total quality management,

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you know, intentional actions towards establishing KPIs, which are key performance

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indicators, and then measuring towards KPIs.

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And so if what you're hearing now is you're like, oh, no, you know,

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the MBAs have taken over and they're going to bean counter us to death.

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Yeah i mean there is some of that there is

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some of that um but please don't think

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what i'm saying is that i don't

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think that an organization can just have a

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cfo run it and have that organization be

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successful because there's a whole bunch of

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intangible things that are very

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very difficult to put a

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quantifiable metric around however in

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the world of ai if there are

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these systems and business process builder integrators people like myself that

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can that understand the facets of the whole business we're not just strictly

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technologists we're people who understand every facet of the business,

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take those people and put them in a position to be able to establish KPIs,

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establish the systems that drive that transparency, right? I said transparency earlier.

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You do have to measure things in a business, but you have to know that the things

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that you're measuring are actually contributing to your objectives without causing

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other negative side effects. I'll give you a great example of this. let's say

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you have a help desk team and their

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kpi is time to close

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the ticket and how many

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tickets they close that week i'm not saying that

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those metrics are not valuable i'm saying that

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if that's what you're evaluating and nothing else

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and you don't have any other controls or oversight

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involved then basically quality

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can go to the toilet because there's those two things that I said you know time

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to ticket closing and how many tickets the person closed that week those are

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not correlated to the problem actually being solved the other thing that could

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very easily get lost in that,

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is you're driving the incentive for a help desk person to ignore or downplay

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something that they noticed that was an indicator of a bigger issue that needed

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to be proactively handled. And how you do that is a subject for another day and another discussion. Yeah.

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So I want to go over this driving your cultural change to operational maturity,

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and thereby you are going to achieve higher profitability.

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And I set the stage here for you about why you really need to be doing this.

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Because you can't be adopting AI without doing this.

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Because you're putting your company's data and your customers' data and your

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employees' data at risk. If you don't do this and then your employees, when you don't have that operational

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maturity and you don't have the controls and guidelines in place,

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your employees become your biggest risk factor.

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And I see it time and time and time again. So let's get into this and I'll probably

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do part two on this because there I'm going to give you a lot of like tangible

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things you can do to get yourself to the point where you're you're ready to go with AI.

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Okay so we've already talked about some of

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the problems that have to do with not having

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operational maturity and those

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things all directly impact profitability and if you're saying oh well we're

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a non-profit you still have to get things done and drive outcomes and stay within

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budget right so that's still profitability if you're a non-profit you're still

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running a pnl you're still trying to be, I hope,

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efficient with the resources that you have.

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And I see this across probably 450 different businesses that I've done consulting

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work with over the last 30 years. All the same problems. They all have the same problems.

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Different variations of it, but they all have the same problems.

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So if you think this isn't applicable to you, my data bank of personal experience would say otherwise.

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They have underutilized resources, which is effectively like lighting payroll on fire.

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That doesn't help anybody. Inconsistent outcomes. So if you're like a customer

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service centered sort of business or you're building product,

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either way, you need to have your

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team delivering outcome consistency in accordance with your standards.

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You need your team to not be engaging in policy violations.

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You don't want them to be engaging in things that increase risk for an organization.

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You probably have some level of compliance that you need to adhere to.

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There are probably circumstances where you have customer contracts that have

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terms and conditions that you don't want to be in breach of contract with your

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customer because your company didn't meet those compliance requirements.

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And compliance requirements are not just simply like a framework.

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It's like, oh, well, we don't have to comply with SOC 2. That's not what I'm

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talking about. You know, it's not, I'm not talking about ISO 27001.

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I'm talking about anything that has been a promise that you've made to your customers.

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Your revenue stream is now contingent upon that.

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Okay one of the other big things that i think businesses really need to be paying attention to.

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Is i see so many bad decisions that have a horrifically financially and otherwise,

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across the board adverse impact when they're afraid of firing somebody they're

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afraid of the adverse business impact due to the loss of somebody that they

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think is a key employee I've seen some of the most deranged,

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destructive things happen to organizations years and years and years because

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they can't get themselves to decouple.

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Their business success from a person.

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And it's all because of a lack of operational maturity. Okay.

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Let's just talk about what you're doing in terms of demand or expenditures that

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you're doing on a monthly basis, typically per employee, without talking about their salary.

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So, you know, we all know that they have salary, there's base payroll,

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FICO, workers' comp, unemployment. There's worker there there's your payroll processing

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expense your hr management expense vacations other

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benefits etc right that's all kind of like derived

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as a function based upon their salary now if you look at like the rest of everything

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else it's you have business insurance you have an office you have some technology

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you know you have all of these tools that you've given to an employee so that

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they can be facilitated to do a job. What I find is that that dollar amount on a monthly basis ranges between $300

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to $400 per employee per month.

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And I'm assuming here that we're talking about people that we're giving a computer

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to, okay? I am not talking about line workers in a factory. So let's just be clear there.

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You know, I'm not talking about people who are retail checkout cashiers, right?

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I'm talking about people that are deemed knowledge workers, you give them a

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computer, and you expect them to use the computer to do things with the computer.

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There's a whole suite of tools that come with that, and that's anywhere from

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$300 to $400 per month per employee, and that is in the U.S.

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Midwest where I'm coming up with those numbers. For a business to be profitable, what they should be doing is looking at their

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fully loaded cost from that employee on a monthly basis,

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so salary and all of those other things I talked about, you know,

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plus their per month fees that are other indirect, indirect expenses.

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And they should be doing a three to four X multiple of that employee to say,

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okay, well, we have to cover SG&A.

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We have to cover a lot of other business expenses that are associated with our operations.

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And each employee needs to contribute towards that. So that fully loaded cost

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on a per month per employee basis, take three to four X of that.

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And that is the kind of ROI that you should be getting on a monthly basis from each employee.

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And if you're not, then, you know, that's a problem.

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So it's almost always a combinatory product of things that the organization

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needs to be doing better and things that the employee needs to do better.

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So there's a shared responsibility model towards profitability for darn sure.

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But if you're going to try and get your hands around this and start to get motivated

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about it and start to drive cultural change through your organization to make these things happen,

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And getting some metrics and getting some understanding about the amount of

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money you're lighting on fire, it matters a lot.

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I mean, I've seen circumstances where a single employee is the reason for a

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massive breach that costs a company, if not hundreds of thousands of dollars,

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way more than that, you know, hundreds of millions of dollars, one employee.

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And i've also seen plenty of circumstances where due to a lack of operational maturity,

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and due to an executive management team who wants

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to put entirely too much trust in one person they will light hundreds of thousands

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of dollars on fire and won't even bat an eye about it and that in my opinion

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damages everybody else in the organization so that's a deficient leadership, in my opinion.

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Even non-profits, you want to be efficient so that you can provide wage increases

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while remaining within budget.

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And we also want staff to continually improve their skills to warrant being

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the recipient of a pay increase.

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You know, they want pay increases each year. Well, we need them to improve their skills.

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So all of this is about utilization and utilization matters in an organization.

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This isn't just about the profitability of a company.

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This is also about employees should be thinking that they should be motivated

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to do these things and help the organization along this effort as well,

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because that correlates with them getting a pay increase.

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So out of time for today, and I'll cover the rest of this in part two.