The IoT Platform Jigsaw – Buy or Build? (Part 2/4)
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In this instalment we explore how commercially available platforms, including M2M platforms, might be an option for you.

Once Upon a Time – A Small Group of M2M Platforms

M2M Service Providers have been using the term M2M Platform for years with their enterprise customers. The main functionality of these carrier-grade platforms was to manage connectivity through a secure, fast and reliable private network via dedicated hubs directly into each of the major network partners.  They allowed control of multiple network SIM estates, management of SIMs and devices and finally management of their billing administration in line with their own systems and procedures.

Most M2M Service Providers developed in-house M2M platforms but also in parallel they acquired  M2M platforms from vendors such as Cisco Jasper Control Center, Ericsson Device Connection Paltform (DCP) , Cumulocity, and Telenor Connexion , among others.

With the hype around IoT, M2M Service Providers become more interested in offering their enterprise customers an IoT application development environment that can reduce time, cost, and complexity of deployment of solutions, that can optimize their business processes and help them deliver better and faster services.  An early example was Etisalat leveraging ThingWorx IoT Development Platform, announced in 2015.

Which brings me to a mobile network operator (MNOs) – Can they avoid the temptation to develop their own IoT management and application platforms? The complexity of IoT value-added service (VAS) development and deployment demands a continuing operational and commercial effort.

My recommendation: MNOs should instead consider partnering with well-established technology vendors in order to accelerate time to market and create customer value through innovation.

Buy or Build an IoT Platform – Making the Right Decision

Technology companies have spent years adapting their sales pitch to convince their customers or potential customers of the advantages of buying commercial products or ultimately IaaS, PaaS or SaaS platforms. On the other hand, many companies across industries see a risk that their business will depend on suppliers and fear being captives of these technology providers. Their management team and tech leaders have found enough arguments to develop their solutions from scratch.

The eternal dilemma, whether to build from scratch or buy a commercially available off-the-shelf (COTS) IoT Platform to support the needs of the enterprise will continue for a while. Here’s what you need to know about both approaches before making this critical project decision.

  • Step 1: Validate the need for an IoT platform. Focus on validating that a business need exists prior to deciding and estimate the return on investment (ROI) or added value.
  • Step 2: Identify core business requirements – Involve the right business people. This will determine the success of the process.
  • Step 3: Identify architectural requirements – It is extremely important to identify any architectural requirements and follow the status of the confusing IoT standards world, before determining if a COTS or custom solution is the best choice.
  • Step 4: Examine existing IoT Platforms – At this point, a business need has been pinpointed, ROI has been estimated, and both core business and architectural restrictions have been identified.  Now, you should take a good look at existing IoT vendors (a short list of IoT platforms, to be more concrete).
  • Step 5: Evaluate your in-house skills to support a custom IoT platform – It takes many skills to design and deploy a successful IoT platform that is both scalable and extensible.
  • Step 6: Explore if a COTS IoT platform fits your need – If your organization does not include a development group comprising personnel experienced in designing IoT solutions to support your enterprise-wide business solutions, a COTS IoT platform will probably provide the best long-term ROI.

More considerations for choosing an IoT platform coming up in the next

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The IoT Platform Jigsaw (Part 1/4)
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When I published “It’s an IoT Platform, stupid!” in 2015 , I did not think that it would be one of my most visited and shared articles.  I am proud that just in LinkedIn, this article has received more than 8,000 visits. That´s why I have chosen an update of that article to initiate my collaboration with Ecosystm.

When in late 2013, I decided to relaunch my company OIES Consulting with a focus this time on Advisory services for Internet of Things (IoT), I thought the selection of IoT platforms would be one of the most useful services that we would offer and certainly one that would bring more benefits to the clients wishing to accelerate the adoption of IoT.

At that time, I had identified about 60 IoT platform vendors and despite guidance from research firms, the confusion was brutal. Today it is worse – there are more than 600 platform vendors and the expected market consolidation still has not arrive. Like other analysts and bloggers, I tried to maintain, classify and publish a list of IoT platform vendors but it looks like an impossible task. However, it is a matter of 2-3 more years.

You must agree with me that the IoT platform market needs a quick and urgent consolidation. Hopefully, in the magical year of 2022, we will be talking about no more than 50 vendors at the most.

The Confusing Market of IoT Platforms

But first things first. How to define an IoT platform? How to differentiate between a Connected Device Platform (CDP) and an Application Enablement Platform (AEP) and an IoT Middleware and a Service Enablement Services (SES) platforms?

Not All IoT Platforms are Created Equal”, it has been said before, and we must understand that the current generation of IoT platforms probably represent the first iteration in this space. But there are marked differences between the different types of platforms. As an organization looking to embrace an IoT platform, this initial diversity can result very confusing. Sean Lorenz from Xively rightly said that the “IoT Platform” is such an overloaded term that its meaning has been lost. Chipset manufacturers, sensor manufacturers, software vendors, consortia and system integrators all have their own definitions.

We find out there with a large number of companies that offer us IoT platforms in the cloud or on premises; for horizontal or vertical implementations; for embedded software development or industrial applications development; with data capture and real-time analytics capabilities;  with devices and protocols management capabilities; with connectivity to any network; for developing applications for smart homes, for smart cities, for connected vehicles, for wearables….. the list continues! Tech buyers are understandably confused in their choice of IoT platform. The global Ecosystm IoT Study reveals this confusion.

 

In such circumstances it is preferable to avoid arguments about which is an IoT platform and how we categorize them. My recommendation here is to ask for help from specialized IoT consultants. They will be able to give you specific guidance based on present and future business needs and can help in the IoT platform selection.

Over my next few blogs I will attempt to guide you through the significance of the different kinds of platforms. It will surely help you in your IoT platform choice, keeping the needs and capabilities of your business in mind.

Stay tuned!

 

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Ecosystm Predicts AI
Ecosystm Predicts – Artificial Intelligence in 2019
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Artificial Intelligence (AI) will change the way businesses operate, and the way customers interact with your company or brands. It will also create new markets and eradicate existing ones. 2019 will be the year that some AI technologies approach mass-market adoption. It will also be the year that businesses start to sort out their data requirements for AI, amid a complex data privacy regulatory environment. But most of all, 2019 will be the year that AI starts to impact employee and customer experiences – from the board room to the living room. Our top five predictions for 2019 are:

Machine Learning and IoT Sensor Analytics Will Drive AI Growth In 2019

The Global Ecosystm AI Study shows that the growth in AI over the next 12 months will come from Machine Learning (ML), as this capability is applied to a plethora of problems and challenges across the business. IoT Sensor Analytics will also see strong growth – due to the growth in IoT implementations and subsequent exponential growth of the data coming off these sensors and the desire to do something intelligent/different with this data.

The Growth in IoT Will Fuel the Growth in AI

Today, many organisations are deploying IoT solutions. These sensors are already creating – and will continue to create large amounts of data. While these sensors today are, for the most part, one-way (i.e. collect and analyse data), we are getting closer to the point where many of these sensors will be bi-directional (i.e. sense and respond). Businesses will look to AI tools – particularly IoT Sensor Analytics and ML – to help them learn from that data and respond accordingly. In many ways the future success of IoT and AI are interdependent.

In the Short Term, AI Will Create More Jobs than it Removes

Much of the media focus on AI has been around the jobs that will disappear in economies driven by AI and the automation that it will enable. But in 2019 (and over the next few years), AI will create more jobs than it removes. How is this? Firstly, we are seeing AI do a lot of jobs that are not even done today – analysing images for trends that humans did not see, looking for correlations in data sets that we did not know existed. Secondly, even where automation and AI are driving productivity, the vast majority of organisations are taking the opportunity to reskill those people. AI-driven profit will be ploughed back into businesses and create more employment opportunities – some of which we can imagine today and some we cannot. Thirdly, there is the vast hiring that organisations have started to undertake to bring on board the skills they will need to make their business smarter with AI. Many of these jobs today are in addition to, not replacing existing resources.

Bimodal IT Departments Will Slow Down AI Implementations

Many of the digital capabilities that businesses have been building over the past five or so years have not required active participation by the IT team. What started as “shadow IT” initiatives became the standard way to deliver customer and business value as smart organisations pushed their technology resources into the product and customer teams, so they could drive innovation at pace. But AI initiatives involve training algorithms with data – the more data the better the algorithms. Business leaders will need to work with IT to get access to this data – that typically resides in “back-end” systems – to train their models. At this step, many bimodal IT departments will kick the project into slow mode, because the data sits in “slow mode” back-end systems. The project will be managed with “slow mode” processes, using heavy-handed governance and processes to turn what could have been a six-week project into a six month one.

A Merger of Massive Scale Will be Driven by AI Assets

According to the Global Ecosystm AI Study, Microsoft, IBM, AWS and Google account for 62% of current and planned AI implementations – and that dominance is set to continue for the foreseeable future. This means a lot of other big companies miss out. SAP, Oracle and Salesforce are hoping that AI will help them get deeper within their existing customers and also expand beyond their current client base. Therefore, we expect a massive merger (in USD billions) driven by the AI customers and assets of the technology vendor. Technology companies that are used to dominating their industries – Cisco, HPE, Dell EMC, SAS and others could be left behind if they do not get scale quickly in the AI space – so a major merger is on the cards.

For access to the full report, please follow this link.

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The Repercussions of the Singapore Health Data Breach
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As a health analyst, I have always considered myself lucky that Singapore has been home for the last 9 years, and I have been a witness to the national ehealth initiatives from close quarters. So, when I received the SMS informing me that my son’s name, NRIC (identification number), address, gender, race and birth date are floating around in the cyberspace somewhere it was disconcerting to say the least. True that his medical and financial information had not been breached, but that’s small consolation for someone who took for granted the sophistication of the health records system in Singapore.

A Quick Recap

SingHealth, Singapore’s largest group of healthcare institutions, announced in June 2018 that non-clinical personal data of 1.5 million patients had been “accessed and copied”. Outpatient prescriptions information of 160,000 patients were also compromised. There was no evidence of this breach going deeper into actual patients’ clinical records and the other 2 healthcare groups were not affected. The breach was detected a week later, a relatively short period, but it was not immediate. Security – identification and threat management – is one of the mainstays of any Digital Transformation journey, and Singapore healthcare is considered to be well along on that journey.

It is commonly believed that security breaches are waiting to happen, and that organisations are not concerned with ‘if’ but ‘when’. Moreover, the disparity of the devices used in healthcare makes security a difficult proposition. This will only become more complicated once IoT sensors and devices are used from outside the walls of hospitals. AI-driven breach detection is being portrayed as the hope for the near future.

Why does this continue to concern me, even after 5 months?

  • A cautious approach to NEHR. One of the first statements that the government made in the wake of this disaster was that the government is reviewing the ongoing NEHR initiatives. Since then, the Cyber Security Agency (CSA), and PwC have been appointed to identify the weaknesses in the NEHR initiatives, with a view to address them. It is a good time to re-evaluate the possible weak links before going deeper into the program.
    But, almost 10 years after the NEHR was launched the country has still not been able to realise the full potential of the initiative, especially because of limited participation from the private sector. Will this lead to a conservative approach to creating the ‘One Patient, One Record’? Will this put on the brakes to ongoing progress of the ehealth initiatives?
  • Private Participation in NEHR. The private sector accounts for 80% of Singapore’s primary care. It is possible for a citizen who has never stepped into a public polyclinic, choosing the friendly, neighbourhood GP instead, and has had no acute care needs (whether inpatient or outpatient) to not be on the NEHR system. And this would include chronic disease management, which is the primary cause of concern in sustainable healthcare. The Singapore Personal Data Protection Act 2012 (PDPA) law governs the collection, use and disclosure of personal data by all private organisations. The Act, that came into effect in 2014,  states that organisations that fail to comply with PDPA may be fined up to $1 million and public reporting of the breach. However, the public sector is not included under the PDPA! So in effect the public healthcare consumers whose data was breached have no recourse under PDPA. But this might deter private healthcare providers with very rudimentary IT systems in place, who are liable under PDPA. The government has already been fighting a reluctance on the part of these private primary care providers to go digital with the patient records, and sharing them with the public system,  with a view to build a more comprehensive NEHR.
  • ‘Smart nations’ need ‘Smart’ citizens. This has been my mantra regarding Singapore’s Smart Nation initiatives for a while now. And smart citizens are not necessarily only those with access to multiple mobile devices and wireless connectivity. Smart citizens are also people who are aware of the pitfalls in the journey, and of their rights as they travel together with the government on the ride.
    What shocked me was the singular lack of concern among the average Singaporean, when I tried to discuss the gravity of the health data breach – which is considered even more dangerous than financial data breaches in most mature countries. The common response I received was that its only personal data. Well, your national identification number, along with your date of birth, in the hands of nefarious agents can do a lot of mischief, I reminded them. And what about the prescription data, I persisted. That got answered by a view that prescription data is not really health data! A lot can be inferred from your prescription data… I persisted with no avail! Healthcare is moving toward giving autonomy and control of health records to individuals. To be able to leverage this control, individuals have to be a) concerned about their health and wellness parameters b) ready to record and share their health data with the right people at the right time, and c) aware that health data is private and needs to be kept secure.

There is no doubt in my mind that Singapore will do all within its capacity to avoid a breach of this level – and other industries are feeling the repercussions too. But the government definitely has to manage the private participation in NEHR more delicately and diligently, in light of this breach. They also have a long way to go in educating the citizens on the privacy and compliance angles to health data.

 

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IoT is a Strategic Initiative – It’s time to Rethink Business Models and Cut Waste to Sustain in a New Era
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There have been several productivity improvement techniques such as Kaizen, Total Quality Management (TQM), Business Process Reengineering (BPR), Lean Manufacturing, Lean Thinking, Lean Maintenance, Six Sigma, ISO Certifications and Business Process Management and others. These waves of productivity improvements focused on certain core principles such as:

  • Cutting waste from processes
  • Bringing transparency to decision-making
  • Empowering users through better involvement and cross-functional information
  • Improving quality, cutting costs, improving business velocity and improving customer satisfaction

These productivity improvement initiatives provided incremental benefits to the industries where they were implemented. However, companies often were satisfied  with the marginal benefit they could manage to derive from their business improvement initiatives.

How Productivity Improvement and Enterprise Software Solutions are Implemented?

In the last 20 years, enterprise solutions like ERP, SCM, HCM, and CRM were at the forefront of digitising business processes. Many companies have tried to implement these solutions without a thorough analysis of achieving real business outcomes and deviations from current business models. As a result, there have been many cases of wasted investment and time, where software solutions have been implemented with little to no additional gains.

To eliminate the risk of such technology implementations, while at the same time better manage the projects, an array of implementation methodologies has been designed by consultants. Positive collaboration between a company and its consulting partners yields positive results. However, such high-level revamping of business models has not  been considered mainstream in traditional industries.

Startups on the other hand have experimented with new business models. We have all seen the emergence of new industries such as eCommerce and eGovernment and new initiatives such as Online Advertising, Mobility Apps, and Internet Banking. In many ways, these industries have brought significant changes in our life. In the coming era, we perceive the need to bring changes in the business model in conventional industries.

Emergence of IoT for Process Improvements

One of these new technologies companies are implementing is Internet of things (IoT). Many companies are considering the implementation of IoT solutions in a variety of different ways. These companies need to justify their projects and apply deep thinking for value creation. To bring process value, we need to answer questions such as:

  • What is the purpose of a process?  
  • Can we eliminate it? If not, can we simplify it?
  • Can we do the process in a better way?
  • Can we improve the quality of product, process and relationships?
  • How can my processes add better value to the company?
  • Can I create better outcomes?
  • Can I implement IoT now and create a differentiator?

IoT in a true sense is much beyond the installation of sensors on products, equipment, locations and people. IoT includes a myriad of solutions such as asset tracking, predictive maintenance, remote diagnostics, chatbots, drones, machine learning and artificial intelligence – the list is almost endless. In a fully-fledged IoT implementation, machine-to-machine communications would be used to eliminate human errors and provide rapid decision-making. The challenges of IoT entail integrating multiple partner’s product stacks into your solution while keeping it seamless for your end-user.

IoT implementations are iterative in nature and therefore the best implementation practices have yet to be evolved. We have formulated methodologies that trigger value creation validation at every stage of the methodology i.e. from the Ideation Stage to the Deployment stage. We need to create the value not in terms of incremental benefits but also changing the business model of the company itself. Start-ups challenge traditional giants not by evolving incrementally but by providing revolutionary new advancements. New business models would need to be delivering improved value to the customers in a much more personalised manner. New business models will need to address new pricing strategies as well as new positioning, new partnerships, new order fulfillment structures and new modes of customer value delivery.

Rethinking Business Models

Companies need to seriously think about an IoT project as a strategic initiative. IoT can immensely help companies in deploying creative ways to become efficient. IoT implementations cannot be approached the same way as a software implementation. In an IoT project implementation methodology we would not only focus on processe improvement and cutting waste, but we would also ask fundamental questions about the way relationships are maintained with the customers and within the company. While implementing an IoT solution, we need to make sure that we have answered some tough questions regarding  our business. Secanarios such as this could arise:

Currently a train manufacturer sells trains to the railways. Railways then become the equipment owner with full responsibility of operating and maintaining the trains. The railway’s real job is to transport people from one place to another. However, a huge chunk of resources is spent in maintaining the trains and assuring high reliability. With IoT, the maintenance may be outsourced to the equipment manufacturer. All operations and maintenance data is captured in the system and the equipment manufacturer is a party to providing reliable service. With the maturity of technology and acceptance, a time will come when railways will ask, “What is my real business? Is it operating trains or is it maintaining trains? Can we collaborate with the equipment manufacturer to maintain the train? How do I know that the equipment manufacturer can do the right job and assure high reliability?”

These questions are difficult to answer because of the separate value models assigned to the ecosystem partners. However, IoT technology is changing business boundaries. Train manufacturers and train operators can now start thinking of offering new business models by remotely predicting and diagnosing faults. Over a period of time, with trust having been established, railways and train manufacturers can even think of changing their pricing model based on the number of passengers being carried, or distance travelled with incorporated reliability standards.

This is a simple model in which an IoT product enables value creation through closer relationships between supplier and customer, and by rethinking the ways current business models need to be tweaked. When we design the new business models, we should surely ask some relevant questions like:

  • Is my IoT business model cutting costs, improving productivity, improving user motivation and/or increasing revenue?
  • How are new delivery models eliminating or reducing inefficiencies?
  • How am I collaborating with the players I never thought of collaborating with earlier?

The future holds a new era of high productivity. Moreover, a plethora of new industries will naturally sprout with the emergence of new business models created due to technologies such as IoT. Companies should closely focus on value creation using new business models and align all resources as required by the new business model.

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There Is No IT Skills Crisis – We Just Need To Train Our Existing Staff
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I regularly hear CIOs and other tech leaders complain of the IT skills crisis – that it is hard to recruit new people, they are too expensive, and that they are hard to retain. But at the same time, Australia Bureau of Statistics data points to the fact that, while the number of people studying IT-related courses is dropping, graduates are finding it hard to get a job – and for every job advertised in IT there are 29 candidates per open role. Despite all of this, I would argue that we don’t have an IT skills crisis – we have a training gap. A big one.

Just in the Sydney market I was recently told by various industry leaders that over the next few years there will be a shortage of AWS skills in the market – by up to 2,000 people. The same can probably said for Azure skills, security, DevOps, data scientists, and Google Cloud Platform. However, assuming 30 in a training group, and a week-long course, the AWS gap could be closed in 15 months by a single training provider – in less time with it spread out across many providers. Yes – some might need more training (weeks or months), but others could need less.

In the battle to keep up with market demands, I regularly see CIOs, Applications, and Infrastructure leaders bring in expensive contractors and consultants to make up for their skills gap. You KNOW what skills you will need. You WILL have some of your applications and infrastructure in the public cloud. You WILL need AI expertise. You WILL need more security professionals. You also know what skills will disappear or have less demand – and if you don’t, get on a call or catch up with a peer in the industry who has made the move to a modern, cloud-based development environment.

The costs of training should be in your budgets today. You should be having conversations with your infrastructure professionals about what skills they will need in the public cloud world – some might make the leap to DevOps pros, others Automation Engineers. You should be upskilling your developers to become BizDevOps pros. Put them through Design Thinking and Customer Journey Mapping training. Have them spend more time with the product, service, or CX leads. Retrain some of your QA professionals to become quality AND monitoring professionals – get them involved in live systems, as it will enhance their testing skills. Work with your DBAs to understand the skills they will need to transition to, and manage public cloud databases.

Most of the people you need already work for you – they just need the skills that will take them and your business forward.

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The CIO Role As We Know It Will Disappear
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Have you noticed how IT shops are changing? ANZ Bank, BankWest, William Hill, REA, Sportsbet and many other organisations are restructuring their technology function – moving many of the functions that impact the product or customer experiences into the teams that are responsible for that product or the customer experience. These business restructures often go well beyond an IT change – it is usually about putting all of the resources that can impact the customer outcome into the same team in order to be able to drive change at pace. Some take it even beyond the customer and product teams, and move HRM to the Employee Experience team, ERP to the Finance team, CRM to the sales/marketing team/s etc.

So the question needs to be asked – if most of your IT team has been moved to the business teams, what is the role of the CIO? And the answer to that question, most of the time is “there is no role for a CIO”… In fact, many businesses that have made this move no longer have a CIO. When REA made the change, their CIO became the Chief Inventor; when William Hill combined IT and Product, the CIO effectively became the head of products.

But this doesn’t mean there is no role for the CIO – some will see the opportunity to embrace their technical side and become a “Chief Engineer” – as many businesses will maintain some technical capability in house. Some will become the head of Employee Technologies – your information and other workers will still need end-user computing devices, tech support etc. A potential pit stop role will be head of Digital as some companies are giving the responsibility to drive digital transformation to a senior executive (but as mentioned this role is just a pit stop as being digital quickly becomes everyone’s responsibility – not just that of a senior executive!). Some will embrace their passion for innovation and lead the big changes that the business will need to face, and others will step up to a senior management role within the business – possibly managing change, implementing automation, or another new competency required of the business.

So as a CIO you need to start mapping your future journey – when will your company or department embrace the “fast & innovative” approach to business and restructure around products or the customer (some call it the “Spotify model”, others the “software model” – but either way it is about being able to deliver customer value at pace)? What will your role be in the transition? And what will your job look like after the change? I recommend you drive this change and become a master of your own destiny – I know some who CIOs who had this change forced upon them, and it did not end well for them.

I have helped CIOs and their teams with this transition so please reach out if you are interested in having Ecosystm help your business become fast and innovative in order to drive better customer outcomes, and help your CIO and IT team to create a new digital-ready future.

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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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