10 Steps to Digital Transformation
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Digital transformation has become the talk of the town. Over the last decade, organisations across the world have pushed towards digitisation – at first to share information, before moving on to relationship-building via social media and direct commerce.

Buyers have become more informed and savvy, and often have unfettered access to alternative sales channels, creating an increased need for companies to up their game – particularly those who didn’t start life in the digital space.

Indeed, a successful digital transformation has become essential for traditional incumbents to compete with young, digital disruptors, who are often cheaper and more nimble. So businesses scramble to deploy new technologies in the hope they’ll gain back their competitive advantage.

However, industry figures suggest that 9 out of 10 digital transformation projects fail – half, spectacularly so. Clearly, something is going wrong.

Using Ecosystm insights based on interactions with technology buyers from multiple industries, along with secondary research, I’ve come to the conclusion that any attempt at digital transformation should adhere to the following 10-step plan.

1. Know Your Purpose

Before embarking on any digital transformation project, ask yourself ‘why’?

Most cases are triggered in response to market changes, whether that’s changing customer demands or an evolving competitor landscape – and that’s not a bad place to start. However, it’s rarely enough to sustain a project, because that in itself is not a purpose so much as a knee-jerk reaction.

Purpose should be something that provides a tangible benefit to the organisation – for example, productivity gains, efficiencies or access to new markets and market segments.

2. Begin With Customer Needs

The best place to start defining your purpose is almost always related to customers or end-users. Disruption is everywhere, but it only takes place when players tap into a need among customers previously unmet. Businesses must therefore identify these needs, even if these needs are those of internal “customers” i.e. employees. These needs may change as you progress and you should be open to re-evaluating projects to keep pace.

3. Build A Business Case

The business case is essential for securing buy-in from senior management To convince them, you’ll need to be clear, concise and in line with the priorities and strategy of the organisation. You should clearly state objectives and anticipated results, as well as potential consequences of not implementing the project. A good business case should instil a sense of urgency.

4. Define Success

If your reasoning for digital transformation is well-founded, key success criteria should be relatively easy to define and closely-linked to your purpose. It’s also important to consider successes that relate to the implementation process itself, which can often be difficult and time-consuming. These criteria could include business satisfaction, team involvement and employee engagement or training. Make sure that all criteria measurable. That way, you can measure and share successes throughout implementation to maintain leadership support and demonstrate accountability.

5. Secure Leadership Champions

Transformation projects often face stiff internal resistance – so it’s critical to get members of senior management on board with the plan to see it through to fruition. Chances are that you will need more than just their approval, and that they’ll need to actively support and drive the project with you.

6. Get Funded

Yes, like any other complex IT project, digital transformation requires proportionate investment – both monetary and resource-wise. Make sure the whole project is funded from the outset, and that the organisation understands the full implications of the project including, wherever possible, an overview of hidden costs such as temporary drops in productivity. This implies that all relevant business units should be involved from the early planning stage, and their input incorporated into the overall plan.

7. Manage Stakeholder Involvement

That said, be careful not to end up in a situation where you have “too many cooks”. Different business units will have their own agendas and may well not agree with the priorities or even the strategic focus of the project. Others will have urgent needs that make them push for short-term or stopgap solutions, so you’ll need to be able to manage their expectations. Also, make sure you communicate your purpose when dealing with external partners, and be ready to manage them just as you manage internal stakeholders.

8. Watch Out For ‘Legacy Roadblocks’

Your interactions with stakeholders will give you an opportunity to identify the potential ‘legacy roadblocks’ in the organisation – not just in terms of technology, but also individuals who may become obstacles due to ‘legacy mindsets’, accustomed to and comfortable with the old way of doing things. Learning how to navigate them may prove essential to the project’s success.

9. Develop A Project Narrative

Digital transformation projects can cause considerable anxiety among employees. If the project involves restructuring, consider developing a narrative to help communicate and clarify the effects of transformation. This narrative should tell a compelling story of how market dynamics are changing, why transformation is therefore necessary, and what impact this will have on the organisation. It won’t necessarily soften the blow of redundancy, but it will help explain why the situation is unavoidable and minimise opposition.

10. Never Settle

Digital transformation never ends. The whole point is to be able to respond to the ever-changing dynamics of the market, and that means you can’t rest on your laurels. Keep your ear to the ground and continue to collect feedback from customers and stakeholders so that you can make continual adjustments.

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An IT Operating Model for a Digital Age
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Speed and innovation are at the core of any successful business today – with power placed increasingly in the hands of digitally-savvy and fickle customers, the pressure to continuously improve products and services has never been greater. If they’re not delighted by each and every interaction with a brand, today’s customer simply moves on at the click of a button or swipe of a screen.

For digitally-native businesses – for example, Spotify or AWS – this competitive, customer-focused spirit is in their blood. But otherwise, most traditional businesses today are not set up to deliver a great customer experience. Bogged down by traditional organisational models, they are instead structured more around cost efficiencies than innovation.

Think, for example, of a typical IT team – generally, all tech staff will sit in their own division, removed from the rest of the business because it’s easier to track, manage and budget their work. What happens, then, if the Head of Customer Experience has a request? It’s unlikely they’ll have much interaction with the team, and probable that they’ll be answerable to different KPIs than IT. The result is often two frustrated parties lacking a common language and unable to deliver innovation at the pace required by customers and the wider business.

The challenge is to reorganise team structures in a way that allows for innovation to flourish. In the era of Digital Transformation 1.0, that meant a bolt-on or ‘bi-modal’ approach to digital, essentially giving a dedicated team the resources and license to operate at pace, while the rest of the business continued plodding along in a traditional environment. It’s not a bad place to start to get digital initiatives prioritised, but the reality is that ‘digital’ now impacts every transaction and every touchpoint.

For example, even if customers go into a bricks-and-mortar store, it’s likely they’ll have first researched products and compared prices beforehand. Meanwhile, on the business side, sales & marketing teams are now using aggregated data insights to inform their campaigns in the hope of shortening sales cycles. Or how about airline passengers – how many people do you think would go into a travel agency? Now, we can book our flight, seat, meals and luggage online, as well as check-in before we even get to the airport.

This means that a one-dimensional team isn’t enough to change or impact customer experiences. Instead, businesses need to be gathering people from across their organisation – whether that’s Product, CX, Distribution and of course IT – who today have different metrics, budgets, priorities and timelines, and give them the mandate to work together towards one united goal.

In an airline, that might mean moving from a structure where they have logistics, ticketing, loyalty, IT, project management, customer lounges, check-in, and baggage all into a single team called “pre-flight experience”. Every time a change needs to be made to the customer experience before the flight, all the roles that can impact that change can come together easily, knowing that they share the same goals and are driving towards the same outcome.

It’s a divide and conquer approach – instead of putting all the IT eggs in one basket, you send them into the product and experience teams to develop and improve digital services on the ground. The new structure of IT teams (Figure 1) would have:

  • Product and project managers working side-by-side, complementing each other’s skill sets while overseeing the process of developing and improving products, services and experiences
  • Developers embedded in the teams, sitting alongside Quality Assurance to ensure the development of digital services is not unnecessarily slowed down
  • DevOps providing the cloud infrastructure and platform services as required
  • Customer / User Experience teams, working closely with tech to ensure final products and services are easy and intuitive to use, and delight the customer
  • Data Management shared across teams to ensure insights are not siloed, but rather treated as a product and integrated throughout a business
  • Architecture as a guiding function, constantly evolving and improving capability that makes the business better, more efficient and faster

Security, often shared across teams, and given the ultimate power to say ‘no’ if a product could compromise customers, employees or the business itself

 

 

But, where to start? Ultimately, the power to drive changes lies in the hands of the CIO, but will require collaboration across the c-suite as business leaders adapt their relationship with IT and determine team KPIs. It’s also important to provide training to help employees prepare for the new structure.

Once in place, this model could well change the face of IT teams as we know them. For Technology Leaders, the role of the CIO will inevitably evolve – whether they become a technical leader, run innovation and invention functions, or take responsibility for delivering revenue and/or customer outcomes. CIOs who are ahead of this change will be able to shape their role going forward based on their profile – but it’s worth noting that those who have change forced upon them will rarely be in a position to be masters of their own destiny.

On the flip side, for Technology Vendors, this model is likely to bring challenges. By bringing business and tech buyers together into one team, we should see a shorter sales process – but it will also make it harder to find the right buyer in the first place. To further complicate matters, with a focus on delivering continuous customer value, buyers are likely to require specialised solutions tailored to their unique needs and goals. Vendors will therefore have their work cut out to better understand their customers and the outcomes they are trying to drive in order to make the sales process smoother.

This new model of delivering continuous customer value is not perfect – it has inefficiencies, and moves away from focusing on big-ticket inventions towards smaller, everyday innovations. However, it is only through making the transition to becoming a fast and evolving business that companies will maximise their IT and digital capacities.

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FinTech 2.0 – What does this mean for financial institutions?
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The term ‘FinTech’ has arguably taken the world by storm, but the application of technology in financial services ecosystem is not new. What is new are the possibilities being realized as the industry evolves. As technology rapidly develops and advances, more companies are building upon the efficiencies gained with FinTech 1.0 to be more adventurous, pushing the boundaries of current regulatory frameworks and leveraging emerging technologies to redefine the financial product and services ecosystem.

Entering the era of FinTech 2.0, we’re seeing a progressive trend from purely focusing on making things easier, to focus on true innovation. The question is no longer ‘How can I make this process more efficient?’ alone, but more so ‘Where can we make greater positive impact?’ and ‘How can we add real value?’. This is leading to greater financial inclusion, the redefining of stakeholder roles, and improved customer experiences across the board.   

For example the Pacific Financial Inclusion Programme and Rocket Remit are leveraging digital technology and out of the box thinking to offer new products and solutions tailored to a mass market of unbanked communities.

Choice in New Zealand, utilizing the Singapore based Nem.io blockchain platform and participants in the second round of the Kiwibank Fintech Accelerator, has replaced traditional merchant transaction fees with a small donation that is redirected to a charity, essentially eliminating the need for credit or debit cards at participating retailers.

Japan-based WealthNavi, an automated wealth management service and ‘robo-advisory’ of sorts, is a platform targeted at people aged 30-50 to help them develop their own optimised investment portfolio. In a market where traditionally, cash and FX are king, WealthNavi is providing a step-by-step guide to help users understand the best way to invest their money while hedging risk.

Meanwhile, the rise of crowdfunding platforms is providing businesses and individuals alike with additional funding sources. In New Zealand, micro-lending platform Ta Koha is looking to ensure more diversity in the business community by supporting Maori entrepreneurs, change makers and communities in their efforts to raise capital. There have also been calls for legislative changes to be made in Australia in order to empower SMEs and allow them to more readily access funds that are fundamental for growth.

FinTech 2.0 is firmly placing power in the hands of the customer, and their focus on the greater good, with new financial ecosystem players carefully aligning themselves to the needs of the day. The question that then comes to mind is, what does this mean for banks and traditional financial institutions?

Banks are at a crossroads – it’s clear that they can’t stand still, or they risk losing market share. But what is the way forward? Do they collaborate and/or acquire or dare to go it alone?

Collaboration in particular poses an interesting dilemma. Banks are essentially faced with partnering with and supporting the growth of their competitors. However, while in doing so they offer startups the chance to scale, in exchange, banks gain fresh perspectives and insights into market opportunities and customer demands. This leads to quicker advancements in an industry that has otherwise previously been limited by legacy.

There are several examples of this – in Australia, the Westpac bank is investing in fintech startups through a $150 million venture capital fund, while HSBC in Hong Kong launched a FinTech R&D lab in 2016, bringing the city’s total to twelve, including initiatives from Accenture and Australia’s Commonwealth Bank. A number of Singaporean brands, including DBS and OCBC have also introduced open banking, enabling third-party developers to access their APIs for greater innovation. A trend that is making its way to Australia and New Zealand.

The result? Very often, a clever application of emerging technologies to solve broader financial challenges and create new opportunities for players in the ecosystem as well as consumers and the public.

From artificial intelligence supporting risk management and fraud detection initiatives; connected devices enabling seamless and tailored processing of procedures and transactions based on an individual’s lifestyle; and blockchain enabling greater trust as well as its application in offering transparency throughout the supply chain; what’s certain is that emerging technologies are rapidly being integrated into financial product and service offerings. With emerging technologies setting a new bar for personalisation and value-add, banks looking to stay ahead of the curve simply cannot afford to ignore them.

However, whether banks choose to collaborate or develop their own offerings, what’s essential is that this innovation isn’t limited by narrow visions of the financial product and service ecosystem or driven by the application of technology for technology’s sake. In our increasingly international landscape, institutions should be proactively learning from other leading markets across the globe, and utilizing resources such as the World Economic Forum’s decision support questions for Blockchain, to identify both good practices to adopt, and approaches to avoid for a more lucrative system for all.

We’re already seeing ideas-sharing taking place – FintechNZ recently hosted a delegation led by the Lord Mayor of London, before sending a group to London FinTech Week. Hong Kong and Shenzhen will be hosting the world’s first cross-border FinTech event later this year. Meanwhile, Singapore’s FinTech festival counterpart is slated to have a pan-ASEAN focus. And larger, traditional banks with often greater reach than fintech startups are well-placed to offer their learnings and insights.

Ultimately, FinTech 2.0 equals change – with customers more empowered than ever before, banks will need to up their game to cater to savvier audiences. The difference is whether traditional institutions embrace the evolution, or whether the evolution forces their hand.

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How Artificial Intelligence (AI) is Democratising Clinical Diagnosis
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Clinical diagnosis is a crucial component of healthcare services, constituting an estimated 3-5% of overall healthcare spend. It is estimated that about 70% of clinical decisions are taken based on lab results. Development of sophisticated and specialised tests for early disease detection and disease management, and the increasing demand for lab automation are the key drivers of clinical diagnostics market.

According to a first-of-its-kind study by The World Bank Group and the Institute for Health Metrics and Evaluation (IHME) at the University of Washington, that detailed and drew comparisons on total health spending across income levels and geographies through the year 2040 for 184 low, middle, and high-income countries, more resources are expected to be spent on health in the future – with a projected $18.28 trillion, or 9% of global GDP, allocated to health spending by 2040.

The report also predicts a widening health spending divide between the world’s poorest and wealthiest countries. It indicates that many countries which are grappling with the largest and most complex disease burdens will spend the least on health.

The dual challenge for healthcare policy and practice is to:

  • Reduce misuse and wasteful clinical diagnosis in the mature economies
  • Enable greater access to quality and affordable diagnostic tools in the emerging economies

The waste and inequities in global healthcare spend is further compounded by the additional factor of a fast-ageing population – and nowhere is this trend more pronounced than in Asia. According to the World Economic Forum, the aged population in the region will increase from 414 million in 2010 to almost 1.3 billion by 2050, representing two-thirds of the world’s older people.

Example of Disease Diagnosis at Scale and Impact

Diabetic retinopathy (DR), a major microvascular complication of diabetes, has a significant impact on the world’s health systems. Globally, the number of people with DR will grow from 126.6 million in 2010 to 191.0 million by 2030, and it is estimated that the number with vision-threatening diabetic retinopathy (VTDR) will increase from 37.3 million to 56.3 million, if prompt action is not taken.  

A good example of healthcare innovation is IDx-DR, the first AI-based medical device approved by FDA to automatically detect diabetic retinopathy. Images of the patient’s retina are captured by a Topcon NW400 camera and uploaded to a cloud server, where the IDx-DR software resides. IDx-DR is the first device authorised for marketing that provides a screening decision without the need for a clinician to also interpret the image or results, which makes it usable by healthcare providers who may not normally be involved in eye care.

The FDA evaluated data from a clinical study of retinal images obtained from 900 patients with diabetes at 10 primary care sites. The study was designed to evaluate how often IDx-DR could accurately detect patients with more than mild diabetic retinopathy. In the study, IDx-DR was able to correctly identify the presence of more than mild diabetic retinopathy 87.4 % of the time and was able to correctly identify those patients who did not have more than mild diabetic retinopathy 89.5 % of the time.

AI based systems are set to revolutionise healthcare by  providing high quality clinical diagnostics at a far greater scale than before, democratising access to those in need, and at a cost that makes it valuable for all the stakeholders.

Digital Health Ecosystem

The promise of AI is clearly not lost on the industry. Rock Health, the first venture fund dedicated to Digital Health, suggests that H1 2018 saw 193 Digital Health firms raise funding worth US$3.4 billion across America alone, putting funding on track to beat 2017 records.

What’s more, regulators around the world are slowly but surely easing requirements for novel and cutting edge technologies to enter the market – two recent examples include the FDA’s Digital Health Innovation Action Plan and Early Feasibility Study (EFS) programme in the US.

A recent study by Ecosystm shows that the applications of AI technologies in the MedTech space are far-reaching, with current focus areas including non-invasive diagnostics, remote health, clinical decision support and predicting patient risk. This would mean better flagging when serious illnesses and ailments are on the horizon, all the while minimising unnecessary consultations and reducing the workloads of already stretched healthcare professionals.

Source: Ecosystm, 2018. Top Business Solutions Addressed by AI in Healthcare Provider Organisations

What is Holding AI Back Then?

From a technological perspective, senior executives – CIOs and Line of Business leaders– cite integration with internal systems, access to data and cyber security as key challenges. To combat this, countries such as Singapore, Australia and New Zealand are looking at ways to aggregate and analyse digitised patient data in the hope of generating insights to improve clinical outcomes.  More work needs to be done to understand specific concerns of all stakeholders, and resolve those conflicts in a respectful and pragmatic manner.

Source: Ecosystm, 2018. Top Challenges in AI Adoption in Healthcare Provider Organisations

That said, as pressures mount on the healthcare industry to achieve more with less, make no mistake that AI in healthcare is inevitable. We’re in a race against time – China, Hong Kong, Singapore, Japan, and India are just a few of the many countries across Asia that have cited shortages in healthcare manpower over the past year. As the elderly population increases, bringing with them a ream of age-related health issues, the situation is only going to get worse.  So ready or not, it may well be the case that in a few short years, the healthcare industry will consider their AI-driven diagnostic tools as essential as their physical ones.

Closing themes

  • AI is a great enabler to democratise disease diagnosis at a scale, cost and quality never been possible before
  • While still an emerging field. trust is slowly developing. Some of the recent use cases are a step in the right direction
  • Regulatory authorities are supporting the development by enabling and encouraging innovation
  • Governments are removing roadblocks and barriers, in some cases, opening population health data sets to teach AI systems
  • Patients are benefiting from improved access and quality
  • Early adopters among providers are embracing new technology, but with caution – impact on payers is still to be seen
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