
SaaS Growth Podcast · 2024-10-28 · 30 min
Key moments - from our scoring
Substance score
56 / 100
Five dimensions, 20 points each
BAC addresses a specific gap in the SaaS implementation market by combining vendor evaluation, process re-engineering, and change management for mid-market and enterprise clients undertaking go-to-market transformations. Rather than letting vendors lead the conversation, Rod and his team conduct deep due diligence on the client's existing processes, data models, and technology landscape before recommending solutions. The firm operates with exclusive relationships to key technology platforms and uses proprietary methodologies to mitigate risk and ensure on-time, on-budget delivery. Rod emphasizes that transformation success hinges on three layers of risk: process continuity, data model integrity, and organizational change management. He stresses that ideal clients have a clear burning platform, realistic expectations about effort and investment, and strong executive buy-in - because go-to-market transformations essentially perform heart surgery on a company's revenue engine. The conversation covers how no-code and low-code tools shift power from IT teams to business owners, why people change management differs critically from technical change management, and how AI is reshaping marketing, sales, and customer service domains with personalization, prospecting dashboards, and content generation - though balanced with human oversight to avoid bias and maintain authenticity.
BAC is an Australian technology consultancy that helps mid-market and enterprise organizations evaluate, implement, and realize value from single or multiple SaaS platforms - particularly no-code and low-code solutions. It addresses the gap in the market by combining vendor due diligence, process re-engineering, and change management to mitigate risk and ensure successful go-to-market transformations.
Process risk (ensuring core business processes remain functional after transformation), data model risk (maintaining or improving how data serves employees and customers), and change management risk (the organization's ability and readiness to adapt, and whether to implement in phases or all at once).
Change management - particularly people adoption and training - ensures users actually use the new system; without it, even technically well-built solutions fail because employees resist change and don't adopt the tools, making the entire investment ineffective.
AI plays different roles across marketing, sales, and customer service: chatbots and machine learning drive self-service in support, AI-driven dashboards create next-best-step recommendations in sales, and AI generates personalized content at scale in marketing - though all require human oversight to avoid bias and maintain authenticity.
Ideal clients have a clear burning platform driving change, have done pre-evaluation on process and data redesign, have realistic expectations about effort and investment, and - most critically - have strong executive buy-in and leadership alignment, since go-to-market transformations affect the core of the company's revenue engine.
Our reviewer’s read on each dimension, with quotes from the episode.
The episode covers several legitimate operational insights - three-layer risk framework, process-first vs. tech-first thinking, change management vs. tech change management distinction - but dilutes them with extended throat-clearing about BAC's founding story and overly general advice. Most actionable substance clusters in the middle third; the AI section and closing revert to platitudes without depth.
We think of it in three layers. First, there's process risk - ensuring the key processes that run the company remain functional after transformation. Next is the data model - maintaining or improving how data is used to serve employees and customers. Third is change management risk
Technology should be the end state, not the start state. The start is understanding processes and defining them clearly.
The core frameworks - process-first thinking, three-layer risk, change management - are competent but well-trodden in transformation consulting. The guest offers no contrarian positioning or first-principles challenge to conventional wisdom. AI discussion is entirely reactive and generic ('AI is important but needs balance'), with no novel observation beyond repeating common cautions about bias and human touch.
Technology should not be the starting point. Start by understanding your business and processes, and then consider technology as the end state.
Without it, companies risk becoming irrelevant. That said, poorly done personalization can feel generic. The key is lifting the bar for personalization while keeping the human element in areas where it matters.
Rod is a CEO of a consulting firm with stated 30 years of career experience and hands-on track record leading transformations and SaaS companies. He is a genuine practitioner rather than a thought-leader-for-hire. However, the transcript reveals limited depth of his actual operational expertise - mostly consulting process and philosophy rather than concrete wins, failures, or hard-won lessons from scaling product or go-to-market functions himself.
most of my learnings have come from helping mid-market and enterprise-grade organizations migrate through technology and process re-engineering transformation programs
During that time, I've had the pleasure of being on both sides of the consulting fence - either leading SaaS companies in the B2B space or consulting businesses
Very few concrete examples or data points. The Australian energy company process mapping is mentioned but not detailed - no metrics, outcomes, or timeline. No specific client results, failure rates, time/cost savings, or adoption metrics are provided. The AI section references ChatGPT branding exercise vaguely. Most claims remain abstract and unsupported by named cases or numbers.
This was the case recently with a large Australian energy company where we mapped their marketing, sales, and support processes, and they'd never seen a complete picture like that before.
In customer service, for instance, machine learning and chatbots have been game-changers for self-service since around 2015.
Carl asks reasonable opening and setup questions but rarely pushes back or probe deeper. He offers agreeing interjections ('I've seen that happen too,' 'It's great that you help with that') rather than sharp follow-ups. When Rod makes broad claims (e.g., 'adoption is key'), Carl doesn't ask for evidence or counterexample. The AI section is especially soft - Carl raises a valid bias concern, Rod half-agrees, and the conversation drifts to LinkedIn tone rather than drilling into the actual risk or responsibility gaps.
In my experience with larger companies, it's all about risk mitigation. It's great that you help with that because it's not always done well.
So you have a high-performance car but put an untrained driver in without telling them what to do.
Computed from the transcript - who did the talking, and the words that came up most.
Show notes at In this episode of the SaaS Growth Podcast, host Carl interviews Rod Moynihan, CEO of BAC, a technology consultancy in Australia. The discussion covers BAC's mission to assist mid-market and enterprise organizations with technology and process transformations, focusing on SaaS platform assessment and implementation. Key areas explored include risk management, leadership buy-in, stakeholder engagement, and change management. The conversation also delves into the evolving roles of AI and machine learning in marketing, sales, and customer service, emphasizing AI's ability to enhance personalization and efficiency. However, the necessity of the 'last human mile' and human interaction in industries such as financial services and aged care is stressed. The conversation underscores the importance of aligning technological tools with business processes and the critical role of change management in successful transformations.
Transcribed and scored by The B2B Podcast Index.
[Carl] Hello and welcome to the SaaS Growth Podcast . This week we’re here with Rod Moynihan, the CEO of BAC, an Australian-based technology consultancy. So, how are you today, Rod? [Rod] Very well.
Thank you, Carl. Pleasure to be here. [Carl] Thanks for being here. I know it's very early for you.
I'm in Finland, and you’re in Australia. It’s an awful time gap to navigate, so again, thanks a lot for being here. Can you explain to me what BAC is, why it exists, and what sort of challenges it solves? [Rod] Yeah, thanks, Carl.
I guess, as I think about the third decade of my career, most of my learnings have come from helping mid-market and enterprise-grade organizations migrate through technology and process re-engineering transformation programs. During that time, I've had the pleasure of being on both sides of the consulting fence - either leading SaaS companies in the B2B space or consulting businesses that help organizations through evaluation, delivery, and realization of projects. BAC was built because we saw a gap in the market, particularly around how organizations assess singular or multiple SaaS platforms to redesign their processes and then implement them, especially in the no-code and low-code space.
We formed the company about four and a half years ago, with a strong focus on go-to-market strategies for companies, which includes marketing, sales, and service support - how companies serve their customers and provide their products. Four and a half years in, we now have exclusive relationships with certain technology platforms. We also have strong due diligence processes and project methodologies to help companies mitigate risk and achieve high-value outcomes on time and within budget.
That’s why we exist: to address that gap and ensure organizations can manage risk effectively and achieve valuable results. [Carl] What sort of considerations do companies normally have when you come in with these single or multi-SaaS solutions to redo their processes? [Rod] It’s a big question, and the answer can differ depending on the market and industry. It also depends on the maturity of the organization and whether they’ve been through a similar evaluation cycle before.
Typically, when we come in, we’re brought in by one of our vendor partners already engaged with the client, which can sometimes be sensitive. There’s often skepticism from the buyer, as vendors tend to say “yes” to everything, promising that anything can be done. When we come in, the risk is often higher for us than for the vendor. I tell clients early on that when they sign a subscription agreement, the responsibility of delivering results is on us and the client.
So, we push for increased due diligence to maintain risk on our side and to maximize the outcome for the client. Depending on maturity, we see varying approaches to evaluation, but a core part of what we do is dig deeply into the “as-is” state - processes, data models, and the current tech landscape. Clients don’t always understand how to do that level of due diligence, so we lead them through it with assets and frameworks. But often, they aren’t fully ready to go as deep as we need.
This due diligence is a non-chargeable exercise for us, ensuring all risks are managed from the start. [Carl] Of course. In my experience with larger companies, it’s all about risk mitigation. It’s great that you help with that because it’s not always done well.
[Rod] Yes, risk is critical, and we think of it in three layers. First, there’s process risk - ensuring the key processes that run the company remain functional after transformation. Next is the data model - maintaining or improving how data is used to serve employees and customers. Third is change management risk - the organization's ability to adapt to change and whether it should be implemented in steps or as a big bang.
[Carl] Looping back to the tech changes you drive, what needs to be true about a customer for them to need BAC? Where would you want a customer to be for them to be a perfect fit? [Rod] The ideal customer has a clear need for change - a “burning platform.” They need to have done some pre-evaluation around redesigning their processes, data, and customer journeys.
They should also have realistic expectations about the effort and investment required, balancing the impact on their people, time, and budget. Often, we see parts of an organization that haven’t aligned senior leadership with their goals. We need leadership buy-in because we’re essentially performing a “heart and lung transplant” on their go-to-market strategy. It’s the core of their revenue, so full understanding and commitment from leadership are crucial.
[Carl] Given the potential risks of these transformations, how do you go about getting buy-in from stakeholders and the leadership team? [Rod] Good question. One of the big gaps I’ve seen between pre-sales and project delivery is that requirements gathering often lacks end-state clarity. We address this by creating pre-sales assets that draw the executive team into the process.
When we do requirements gathering, we often request more than the client is ready to provide, but our tools ensure that the right people are involved. If we can’t get the necessary buy-in, we usually walk away to avoid excess risk. But once people start to see the value, they typically buy in, especially if the client’s leadership and readiness for change meet our standards. [Carl] It sounds like you work with a lot of non-technical people.
You mentioned low-code and no-code tools as part of your offering. How does that fit into the organizational change and innovation you drive? [Rod] That’s a great point. Ten to fifteen years ago, tech teams often led transformations.
Today, we respect the tech team’s role but focus on the business owner, as they own the business process. Technology should be the end state, not the start state. The start is understanding processes and defining them clearly. Often, the work we do presents clients with a comprehensive process design for the first time.
This was the case recently with a large Australian energy company where we mapped their marketing, sales, and support processes, and they’d never seen a complete picture like that before. It became the blueprint for deciding which tools to keep, replace, or introduce. [Carl] I’ve seen that happen too. Departments often become siloed, creating fragmented processes.
It’s surprising how much is improvised, even at large companies. [Rod] Exactly. These ingrained ways of working become hard to change. When processes are tech-led rather than business-led, it leads to a less effective way of working.
[Carl] In my business courses, we learned that buy-in from the people doing the work is crucial in any tech process. [Rod] Absolutely. We touched on risk, and change management is a big part of that. There’s a difference between tech change management, which ensures tools integrate seamlessly, and people change management, which ensures user adoption.
Adoption is key - if people don’t use the system, it fails, no matter how well it’s built. Many companies resist investing in a continuous change management program, but it’s like putting the right tires on a Formula 1 car - essential for performance. [Carl] So you have a high-performance car but put an untrained driver in without telling them what to do. [Rod] Exactly.
The real work starts with project implementation, and that’s where change management makes a big difference in protecting your investment. [Carl] It wouldn’t be 2024 without asking about AI and machine learning. What role is it playing in your work and these organizational changes? [Rod] In the go-to-market space - marketing, sales, and customer service - AI plays a different role in each domain.
In customer service, for instance, machine learning and chatbots have been game-changers for self-service since around 2015. AI has since supercharged these capabilities. In sales, we’re seeing AI-driven prospecting dashboards that create next-best steps and personalized touch plans without requiring much input from salespeople. Marketing AI can generate tailored content and layouts in seconds, which is huge for efficiency.
However, many companies are still unsure where to start. We play in specific domains, which helps us target AI use cases, but I often hear the same question: “Where do we begin?” [Carl] You mentioned personalization earlier. How important do you think it is for companies to invest in AI-driven personalization?
[Rod] It’s essential. Without it, companies risk becoming irrelevant. That said, poorly done personalization can feel generic. The key is lifting the bar for personalization while keeping the human element in areas where it matters.
For example, in financial services, customers may go through the entire process without human interaction. In aged care, the evaluation is often done by a family member, so human interaction remains critical. It depends on the industry, but balance is important. [Carl] AI can be a black box with hidden biases and decisions that are hard to control.
A human sanity check seems necessary. [Rod] Agreed. We use AI tools like ChatGPT internally for tasks, including branding exercises, where we fed it all our messaging to help reframe our brand. While it was a helpful exercise, ultimately, it needed a human touch for delivery.
I think people can often tell when something on LinkedIn, for instance, has been AI-written. [Carl] Definitely. ChatGPT has a specific tone, and it’s weird to think it’s learning from AI-generated content now. Soon, it’ll be learning from itself.
[Rod] Yes, exactly. [Carl] Thank you again for being here. Is there anything you’d like to add or delve into before we wrap up? [Rod] Just a final thought: technology should not be the starting point.
Start by understanding your business and processes, and then consider technology as the end state. Also, for any major transformation, buy-in and a strong change management program during and after implementation are critical for success. These may sound simple, but they are fundamental. [Carl] Thanks for joining us, Rod.
Where can people reach you? [Rod] You can find us at bac.co or email me at rmoynihan@bacpartners.com.
au, or connect with me on LinkedIn. [Carl] Awesome. Thanks for being here, and to everyone else, we’ll see you next week.
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