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Speaker 1: Welcome to Fear and Greed Q and A, where we

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Speaker 1: ask and answer questions about business, investing, economics, politics and more.

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Speaker 1: I'm Sean Ailman. Australian businesses are under pressure, rising overheads,

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Speaker 1: shrinking margins and a need to embrace AI and technology

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Speaker 1: or risk being left behind. But maybe leaders are coming

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Speaker 1: at the challenge from the wrong perspective, focusing on roles

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Speaker 1: not tasks. Jarah Borman is the director of Strategy at

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Speaker 1: Outrun Global, a great supporter of Fear and Greed. Jarah,

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Speaker 1: Welcome to Fear and Greed Q and A thank you.

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Speaker 2: It's pleased to be here. Nice to meet you, Sean.

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Speaker 1: Now, business under pressure, you know, looking for customers. You've

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Speaker 1: got costs, overheads, that type of thing, competition, a growing

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Speaker 1: gap between effort and output. We all kind of know

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Speaker 1: that story. You're saying this is mostly about visibility rather

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Speaker 1: than capability. Just explain that to me.

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Speaker 2: Yeah, So look, we get it. Businesses are struggling. There's

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Speaker 2: a lot of squeeze. Theres a lot of pressure on margins,

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Speaker 2: increased costs. You've covered a few different aspects there that

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Speaker 2: businesses is a struggling with. We're also going through a

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Speaker 2: transition from the information agent to the intelligence age at

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Speaker 2: the same time, and that's creating a lot of upheaval

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Speaker 2: as well. So from our point of view, there's not

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Speaker 2: a capability problem within businesses. There's just a visibility around

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Speaker 2: what work is actually being done. Once you start to

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Speaker 2: understand that, you can realize a lot of businesses kind

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Speaker 2: of sometimes unintentionally at tanking their own capacity within their

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Speaker 2: organization because they're looking at things in that traditional view,

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Speaker 2: which is cost centers and rolls and roles themselves are

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Speaker 2: very broad. They tend to be a collection of tasks

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Speaker 2: and activity sometimes that have evolved over years until they

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Speaker 2: don't necessarily represent what the core focus of that role is.

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Speaker 2: So the question that we think most businesses should be

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Speaker 2: asking is not what their team needs to be doing,

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Speaker 2: but what they shouldn't be doing. And to understand that,

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Speaker 2: you need to break the roll down into those tasks

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Speaker 2: and activities. And you'll find that this sometimes does and

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Speaker 2: sometimes even hundreds of individual activities within a role, and

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Speaker 2: each of those have different cost profiles and different automation

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Speaker 2: opportunities within them, and so that's kind of the track.

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Speaker 2: Once you identify those activities which are capable within a role,

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Speaker 2: you can actually do them at a lower cost, maybe

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Speaker 2: do them more efficiently or effectively with a specialist that

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Speaker 2: sort of thing. And so actually getting an administrator to

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Speaker 2: come in and pull lots of the work and tasks

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Speaker 2: that the team members are doing can be really really effective.

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Speaker 2: But you don't really see that day to day when

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Speaker 2: you're just looking at things from a role perspective.

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Speaker 1: Okay, so let me break that down a bit. So

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Speaker 1: it's almost like process mapping everything that goes on in

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Speaker 1: your organization and working out what the tasks are.

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Speaker 2: Yes, so it's actually sometimes a little bit more granular

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Speaker 2: than that. So like if we use some terminology and

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Speaker 2: a process classification framework, the task is the most granular

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Speaker 2: piece of work. Then an activity is a collection of tasks,

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Speaker 2: and a process is a collection of activities, right, And

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Speaker 2: so if you actually start to look down at that

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Speaker 2: activity and task level, you can find where there's a

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Speaker 2: lot of overpaying for the delivery of those activity and tasks.

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Speaker 2: You might have really high paid local team members that

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Speaker 2: are delivering those tasks when they actually shouldn't be, and

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Speaker 2: you can deliver them a much lower cost. An example

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Speaker 2: could be like a one hundred and fifty k ear

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Speaker 2: marketing manager who spending four or five hours a week

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Speaker 2: on pulling data together for a report, when they could

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Speaker 2: be focused on much bigger, more strategic activities and that

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Speaker 2: could easily be done at a lower cost.

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Speaker 1: How much of this is an AI issue? So it's

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Speaker 1: kind of come to the fall because it is AI,

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Speaker 1: I mean, and AI are better at tasks I presume

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Speaker 1: than roles. How much of it is AI and how

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Speaker 1: much of it is just the way organizations have morphed?

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Speaker 2: Well, I think it's a really good point. It's kind

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Speaker 2: of both. Right, there's a structural issue that we've got

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Speaker 2: here that if we address that, even without AI, we

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Speaker 2: could be doing a heck of a lot better. Right,

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Speaker 2: So if you even just got a local administrator pulling

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Speaker 2: a lot of these tasks and activities off your more

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Speaker 2: expensive local team, then you could save money and cut

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Speaker 2: costs and be more efficient. Just from that along, then

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Speaker 2: if you look at the rise and access to global labor,

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Speaker 2: you can leverage that and that can reduce the costs

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Speaker 2: even further. And then when it comes to AI, it's

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Speaker 2: very good at doing specific tasks, usually with some human oversight,

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Speaker 2: and so that also gives you a bit of a

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Speaker 2: roadmap towards being able to look effectively at AI adoption.

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Speaker 2: So it's like a lens that you need regardless. But

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Speaker 2: in this environment, when you've got global labor and AI

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Speaker 2: just going through the roof, you actually really can leverage

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Speaker 2: those effectively.

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Speaker 1: So what's the size of the price here for organizations?

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Speaker 1: I mean, not all organizations are going to win as

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Speaker 1: much as others, presumably.

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Speaker 2: Yeah, So like every business is I think that we've

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Speaker 2: looked at, even from very small businesses can take advantage

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Speaker 2: of this sort of thinking and this sort of lens

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Speaker 2: to optimize their processes but optimize their costs, I should say,

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Speaker 2: by working out where tasks should be applied. But the

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Speaker 2: bigger the business, often the longer it's been running, the

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Speaker 2: more process and task accumulation has happened around roles, and

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Speaker 2: the more opportunity there is to kind of re engineer

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Speaker 2: the workforce a little bit and free up that strategic

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Speaker 2: thinking or that revenue generating activity that your team members

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Speaker 2: should be focused on by getting kind of unburdening them,

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Speaker 2: if you will.

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Speaker 1: So if you think of these admin coordination manual processes,

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Speaker 1: I'm sure there's a lot of duplicated effort out there.

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Speaker 1: I saw one of the figures there was at sixty

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Speaker 1: to seventy percent of the operations of a business is

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Speaker 1: involved in that sort of thing. There are a lot

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Speaker 1: of that is the sort of thing where you can

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Speaker 1: actually reduce costs, or if you don't want to reduce costs,

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Speaker 1: just keep the people but actually add value.

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Speaker 2: Yeah, so that's a really interesting point. There's a piece

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Speaker 2: of research that came out last year that's really telling

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Speaker 2: when it comes to came out as a result of

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Speaker 2: like AI adoption, where Asana looked at a thousands of

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Speaker 2: organizations and they found that employees only spend about twenty

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Speaker 2: seven percent of their time on the skilled work that

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Speaker 2: they're actually hired to do. Right, that's staggering. It means

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Speaker 2: like you're only getting thirty percent of the output of

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Speaker 2: your staff using on average, using the traditional role based model.

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Speaker 2: So switching this around and looking at unburdening them and

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Speaker 2: getting the right support in place for them, whether that's

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Speaker 2: through offshare staff or AI or a combination of both,

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Speaker 2: you can quite easily flip that figure around and have

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Speaker 2: a two thirds output. You're not going to get rid

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Speaker 2: of DMin completely, right, but you at least can can

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Speaker 2: really drive into those opportunities and maybe double productivity quite

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Speaker 2: easily just by looking at things this way and getting

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Speaker 2: a bit smarter about where you allocate your resources.

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Speaker 1: So how can you start, Jarah? What you're saying all

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Speaker 1: makes sense, and I think of my own business and

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Speaker 1: you know what we could do. But where do we start?

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Speaker 2: Well, so often the first place to start is looking

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Speaker 2: at repeatable tasks and activities that can be turned into

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Speaker 2: a standard operating process. And that really defines what we

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Speaker 2: would call a remote capable task or remote capable activity.

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Speaker 2: And so if you're able to identify those within the organization,

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Speaker 2: things that someone without any prior training or knowledge could

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Speaker 2: pick up a guide and follow step by step. If

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Speaker 2: you have those things in place, they become things that

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Speaker 2: you can then look at resourcing and either offshoring or

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Speaker 2: getting AI to help you with. So that's where you

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Speaker 2: kind of start. It is like going through and analyzing

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Speaker 2: those activities and it's not specific to any individual role

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Speaker 2: or team. Those activities could be consistent across a wide

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Speaker 2: variety of different roles and just getting a specialist then

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Speaker 2: who owns that process, who owns that activity, can have

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Speaker 2: a really big impact just in and of itself. So

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Speaker 2: that's where data entry, report creation, administration, those sort of things.

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Speaker 2: Even when it comes to marketing teams, you can look

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Speaker 2: at campaign implementation specialists who do all the grinding work

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Speaker 2: associated with setting up campaigns and doing them, monitoring and reporting,

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Speaker 2: or even some of the draft commentary with the support

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Speaker 2: of AI. Those sort of things are all very very

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Speaker 2: powerful when you identify them, pull them off the local team,

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Speaker 2: so to speak, and free them up to really express

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Speaker 2: their skills properly within the organization. It's what we think of.

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Speaker 2: It's an opportunity cost before the term many times over

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Speaker 2: the years, but it's a cost that businesses are paying

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Speaker 2: right now that they don't need to be.

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Speaker 1: What's interesting, Jarah, you've talked about outsourcing as well, and

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Speaker 1: you know, using people better. AI is in a silver bullet.

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Speaker 1: It's not like, hey, let's get AI, things will be grown.

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Speaker 1: It's actually just part of a much bigger puzzle.

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Speaker 2: Absolutely, so AI is. It's amazing what's happening at the moment.

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Speaker 2: There's so much hype, there's so much talk. It's so

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Speaker 2: really daunting. But I listened to the podcast. He had

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Speaker 2: a couple of weeks ago with Kevin Hubner who was

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Speaker 2: talking about AI companies and how much cash they're burning

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Speaker 2: building these models and how far away they are from

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Speaker 2: true accuracy, right and therefore profitability. But the problem is

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Speaker 2: is that you're getting the same thing with businesses that

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Speaker 2: are trying to adopt AI. They're taking that same lens

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Speaker 2: and that they're trying to adopt AI and about ninety

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Speaker 2: five percent of generative AI implementations are actually failing to

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Speaker 2: achieve the production impact. That was a study that came

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Speaker 2: out from MIT last year. That's huge figure, right, So

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Speaker 2: when we look at that from our point of view,

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Speaker 2: we're looking at going, well, what does proper AI adoption

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Speaker 2: look like and how can you do it successfully because

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Speaker 2: it's a big part of what we do, alongside access

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Speaker 2: to global labor. And the best way to think about

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Speaker 2: it is that there are four different stages of AI adoption. Right,

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Speaker 2: there's no adoption at all. So you've got a bunch

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Speaker 2: of businesses in the space that have either not started

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Speaker 2: because they don't know where to start, or they've tried

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Speaker 2: and they've failed and they kind of stepped away from it.

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Speaker 2: I don't know what to do here, right then, you've

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Speaker 2: got stage two right, And first of all, we probably

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Speaker 2: don't want to stay in stage one for too long

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Speaker 2: because things are moving so quickly and there's definitely opportunities there.

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Speaker 2: Stage two is human lad with AI support, right, and

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Speaker 2: that is where you augment a person, you give them

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Speaker 2: access to general AI tools. It allows them to be

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Speaker 2: more efficient, more productive, more accurate. This is a really

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Speaker 2: really good space to be using AI and where the

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Speaker 2: most successful adoption is right now and where we can

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Speaker 2: see it being quite successful for some time. Then you've

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Speaker 2: got stage three. That's where the AI leads and human

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Speaker 2: oversight is required, and you see that with a lot

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Speaker 2: of testing and yeah, then's level four is we've got

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Speaker 2: a full blown AI agent looking after things. Now. What's

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Speaker 2: really interesting is there's a lot of hype around point four,

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Speaker 2: but it doesn't really play out like that. It often

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Speaker 2: falls back to level three with that human oversight because

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Speaker 2: we don't actually have full AGI at the stage right.

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Speaker 2: Good example of that is a very note call this

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Speaker 2: morning on WEYMO and San Francisco. The city's actually having

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Speaker 2: to classify call outs to deal with or waymo cars

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Speaker 2: that have just stopped in traffic and are causing all

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Speaker 2: sorts of problems, and so they have to send out

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Speaker 2: emergency services to move the cars on. And so that's

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Speaker 2: a level of human oversight and cost associated with that

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Speaker 2: type of adoption that, yeah, just doesn't really make a

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Speaker 2: lot of sense, right, but that's the reality of those

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Speaker 2: sort of projects. So where we see it is the

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Speaker 2: best and safest and most effective way to take advantage

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Speaker 2: of AI right now is actually in an AI augmented

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Speaker 2: space where it's human lad where their skills and so

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Speaker 2: on get enhanced by the use of these generative AI tools.

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Speaker 2: Really safe place to kind of play and to deploy

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Speaker 2: and get really effective outcomes from.

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Speaker 1: Thank you very much for talking to Fear and Greed.

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Speaker 1: Welcome now as Jarah Borman, director of strategy at outrun Global,

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Speaker 1: a great support of this podcast. If you're keen to

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Speaker 1: explore the opportunities behind what Jared talked about, outrun have

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Speaker 1: put together a new guide. It's called the Top ten

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Speaker 1: Tasks to Optimize for the Biggest Impact. The top ten

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Speaker 1: tasks to optimize the biggest impact plus the cost savings

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Speaker 1: you can unlock. You can grab it at outrun dot global,

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Speaker 1: slash Fearing Greed, outrun, dot glow, will slash Fear and Greed.

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Speaker 1: We'll put the link in the show notes too. I'm

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Speaker 1: Sean Almer, and this is Fear and Greed Q and

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Speaker 1: I