“Only recently have people begun to recognise that working with suppliers is just as important as listening to customers.” – Barry Nalebuff, Yale School of Management.
The traditional approach to supplier relationships – focused on contracts, performance monitoring, and risk management – has become outdated. In the superannuation sector, this master-servant dynamic limits potential.
The future lies in partnership.
The key to future success lies in transforming supplier relationships into strategic partnerships. By optimising these alliances, funds, and suppliers can unlock significant value and enhance member experience.
Value creation: The paradigm of co-creating value through innovation, efficiency, and exceptional member experiences. Think ecosystems, not just transactions
Strategic engagement: Suppliers are no longer just vendors; they are strategic allies. This demands engagement at the highest levels, where mutual goals and collaborative strategies drive success
Mutual Trust and Transparency: True partnerships thrive on trust and openness. Share insights, challenges, and goals to foster a culture of mutual growth and resilience
Balanced focus on Cost and Value: Shift the focus from short-term cost savings to long-term value creation. Understand each other’s business models and work together to build sustainable, mutually beneficial strategies
AI Integration: Leverage AI to revolutionise vendor management. Automate processes, enhance decision-making and create smarter, more efficient partnerships
In superannuation, members are central to supplier partnerships. Regulatory pressures demand cost reduction, faster processing, and improved services. Partnering with suppliers fosters innovative solutions for members, benefiting both the fund and the supplier. This member-centric approach ensures that the ultimate goal—enhancing member outcomes—is always in focus.
As W. Edwards Deming said, “Let us ask our suppliers to come and help us to solve our problems.” The future lies in strategic partnerships, where everyone benefits.
Successful vendor management now requires a proactive and forward-thinking mindset. Organisations must shift from a transactional approach to a relational one, fostering an environment of collaboration and shared goals. This means investing time and resources into understanding each supplier’s strengths, challenges, and potential for innovation.
The importance of cultural alignment between organisations and their suppliers cannot be overstated. A shared vision and values foster stronger, more resilient partnerships. Open dialogue, regular feedback, and mutual respect are the cornerstones of this relationship.
The future of vendor management is in strategic partnerships.
Written by Leigh Bell and Shane Barnes
For more information please feel free to contact Shane at sbarnes@iqgroup.com.au and Leigh at lbell@iqgroup.com.au
One of the fundamentally flawed assumptions we may be working to is that (as for most of history) People use technology…
We are on the cusp of working in a business reality where we must lead, manage, and make decisions in an environment where Technology uses technology in significant manner and scale.
Consolidation and more complex service architectures are driving FSI organisations to greater automation to cut cost and increase the efficiency of digital channels, and therefore, stand up Centaur Teams (people teams enabled by generative or predictive AI).
Establishing how efficient one application of technology is over another is, or indeed how technology can become inefficient as new connections (e.g. API’s) and features are added, itwill become increasingly difficult.
Moreover, applying traditional Lean Six Sigma efficiency analysis to uncover NOISE/MUDA/WASTE/EXCESS CAPACITY needs to address the nuances of technology service provision, not just taking the total cost of IT and dividing it by FTE/Customer/Volume.
This shift demands an informed approach to analysing operations with technology… Technology is no longer just an extension of human capability; it is an autonomous decision-maker, fundamentally altering the landscape of our operations.
Uncovering and understanding the hidden costs of technology is vital for being able to design, develop and evolve operating models. As we have said before a Modern Operating Model must foster adaptive capabilities, regularly review processes, and shift continuously to stay competitive.
Building modern models in the context of the above we suggest should include:
Prioritising Technology Investments: Technology is a catalyst for efficiency; smart investments today lead to streamlined operations and sustained growth tomorrow. But these strategic investments hinge on evaluating their necessity, ensuring they do not create undue cost, and that they align with our operational goals.
Analysing Resource Costs: Resource costs often exceed 50% of total operating costs, with over 33% lost to non-productive ‘Noise’ activities (Source: XeP3). It is crucial to scrutinise resource costs, understand how they are being allocated, then strategically automating processes that make sense.
Improving Data Quality: As mentioned in our first bulletin, Automation’s potential is only as good as the data it relies on – ensuring quality data is a non-negotiable to understand the true cost of technology, empowering strategic decision-making.
How can cost be measured to best support a modern operating model?
The XeP3 total cost-to-serve model provides deep insights into resource allocation, technology investments, and operational inefficiencies. This robust framework driven by metrics and analytics to optimise costs, aligns seamlessly with regulations such as SPG516 – Business Performance Review, ensuring strategies are aligned with long-term objectives.
Understanding resource costs and technology impacts needs strong strategic oversight. By addressing these areas, we can help you transform operations, reduce costs, and improve service delivery. At IQ Group we understand this, and with XeP3, can provide comprehensive insights into cost to serve, enabling you to optimise resources and deliver exceptional service to your members.
In the evolving landscape of financial services and technology, executives find themselves under growing scrutiny. The Financial Accountability Regime (FAR) calls for transparency, ethical behaviour, and personal responsibility. But with Artificial Intelligence (AI) integration at an all-time high within organisations a key challenge arises: How do we ensure AI integration aligns with FAR obligations?
As AI continues to evolve, its implementation presents both promise and risk, with generative AI and predictive AI at the forefront of these discussions. These technologies can revolutionise financial operations, yet they also introduce complex ethical considerations and privacy concerns. This isn’t just about compliance—it’s about maintaining trust and integrity in an increasingly digital landscape.
Fred Kofman aptly said; “Power is the prize of responsibility; accountability is its price”.
Amidst the buzz surrounding AI, it’s crucial to recognise that rapid adoption and its potential benefits don’t absolve organisations from their duty to uphold ethical standards and accountability. Key risk mitigations to maintain accountability, trust, and integrity in the AI landscape are humans involved and high data quality:
AI is used to accelerate decision-making and the resultant outcomes. Under FAR, the executive remains the accountable person for the outcome no matter the process to get there. Adopting AI solutions ensures that there is a human involved to approve decisions and mitigates the risk of unwanted and potentially catastrophic outcomes.
The speed to decision as a feature of all AI places an even greater emphasis on data quality. Poor-quality data is the enemy of automation. Bad data in the AI era is (Bad data)2 and can lead to catastrophic outcomes. Accountability in the AI era increases the diligence required to ensure high data quality, again mitigating risk.
Enter the role of governance, the supporter of FAR frameworks.
Governance plays the vital role of embedding accountability into the core of all projects, including AI projects. Governance ensures transparency, ethics, fairness, and responsible decision-making are at the foundation of these projects. Governance can navigate the balance between innovation and risk, striving to prevent unintended consequences and optimise processes without compromising members.
At the end of the day, visibility over risk demands governance. At IQ Group we understand this need as well as the shifts AI demands and can provide comprehensive insight over activities, aligning them with FAR obligations.
Written by Angie Perry, John Hogan, and Mal Collins
It’s no secret that organisations are diving headfirst into investing in automation, seeing its potential to make things more efficient through cutting down manual work to focus on more impactful work.
Superannuation funds are seizing this momentum, with 73.2% investing in data transformation, 69.6% in automation, and 21.4% in AI/Machine Learning (1).
But here’s the truth: Automation doesn’t always deliver the efficiency we anticipate.
To truly benefit from it, we need to take a step back and view it holistically. It’s not about quick wins; it’s about making things within an organisation work together smoothly – from customers through to suppliers, considering costs at every step, focusing on delivering customer needs, and being able to adapt to change effectively.
As Bill Gates aptly put it, “Automation applied to inefficient operations magnifies inefficiency”.
So, why doesn’t automation always lead to efficiency?
Data transformation – Automation relies on things on reliable data. But when we automate critical processes, we can compromise the accuracy, availability, and reliability of our data.
Suppliers – You need your suppliers and partners to be successful. It’s not just about cutting costs; it’s about working cohesively with suppliers to make the process efficient at every stage. Your supplier’s process is still your process.
Customer experience – Customers drive success. Automating the customer journey isn’t just about saving money, it’s about making their experience better to create loyalty and lasting relationships.
Employee experience – Employees shape the future. It’s not about saving time with automation, it’s about empowering employees to innovate in an environment that welcomes new ideas and creating centaur teams (2).
Technology costs – Automation may seem straightforward, but carries additional, and hidden costs that we need to consider when automating.
In short, automation isn’t a magic fix for efficiency. It’s a powerful tool that needs careful consideration and planning to produce productivity over disorder.
Remember – automation today is the standard of tomorrow.
In Super we have grown up with closed loop service environments that have provided us with: Resilience, Scale, and Distributed investment in technology.
And as recently as 18 months ago IQ ran a masterclass in Super fund operating models, which for its time was quite relevant …
However, time, the world, and technology has moved on.
Wave 2 mergers, competition, advice reform, consolidation of service providers, and demand for data have all set the idea of a steady target state under pressure.
It also raises legacy product and insurance complexities that somehow seem to defy our best efforts for standardisation.
Our thinking now is that we need to look at operating models not as destinations, but as change engines that enable us to regularly re-evaluate and evolve our approach.
Stanley McChrystal called it, building for Complexity not for Complication.
The new operating model paradigm challenges us to identify the key factors which help us to understand, assess and respond to our changing environment. All within the context of dynamic strategy, competition and a sandy regulatory landscape.
So, what makes a successful and continuously evolving operating model, admin strategy and technology service platform?…
Culture
Not engagement, benefits, or retention, but the unwritten instructions that drive most of our activity. Research demonstrates that when we map a process, it covers less than 50% of the actual activity within a team. Culture guides the rest, and can be the difference between standing still, and evolving.
Culture (supported by key operating intelligence) supports the adaptive organisational business model and direction.
So will AI bridge any culture gaps? Not likely. Centaurs (AI enhanced human teams) still require us to set in place a model for decision and action that is focussed on our goals and reflects our ethical and commercial compass.
Automation for its own sake just takes you to the wrong place, faster.
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