The Emerging Technologies Hype Cycle

With all new technology, the challenge is when to adopt and make the right investment decision. Do you jump before main stream adoption to gain competitive advantage over your peers or do you wait until there is broad market acceptance of the commercial value and benefits?

A recent report from Gartner, a leading technology research company, identified the fastest moving technologies in its 2012 Hype Cycle for Emerging Technologies.

Many of these technologies (see below), such as Big Data, Cloud and Social Analytics (social CRM) have been discussed in previous posts. One thing was common in that all of the technologies followed a predictive pattern on how the technology is adopted to maximise both impact and value.

Source: Gartner’s 2012 Hype Cycle for Emerging Technologies

Looking to the emerging technology cycle, we are at a new tipping point where a number of new technologies are converging, such as Big Data, Cloud and Social CRM. These new technologies are becoming emedded and are disrupting more established banking business models in their wake. In much the same way as when the ATMs were first introduced in the 1960s, people continued to prefer interacting with a bank clerk until dramatically in the 21st century, with the culture change of telephony, online and mobile banking, most people don’t set foot inside their local branch.

This can be illustrated by looking at one of the emerging technologies on the hype cycle.

Speech Recognition
Speech recognition has the opportunity to converge with a number of other emerging technologies, such as Cloud and Big Data, to disrupt conventional banking channels.

As we saw with the ATM, it may only be a period of time before people find it more efficient to talk to a robot rather than a bank clerk.

Surprisingly research in speech recognition predates the invention of the modern computer by more than 50 years. Alexander Graham Bell was inspired by his wife, who was deaf, to experiment with transmitting speech which ultimately led to his invention of the telephone. Not until the 1990s that computers were powerful enough to handle speech recognition.

The very essence of speech recognition can be distilled down to mathematics – you don’t need to recognise accents or dialects. James Baker, a computer speech revolutionary and founder of Dragon Systems, a leading voice technology company, identified that speech recognition had to calculate the mathematical probability of one sound following another. His algorithms have become the industry standard.

Converging New Technologies
Speech recognition technology is already commonplace in call centres, where it lets users navigate through menus and decides when calls should be handed off to a real customer service rep.

We are now entering a second technology cycle, with speech recognition being propelled forward as it converges with a number of emerging technologies such as consumerisation and Big Data to provide new commercial benefits.

All speech recognition is highly dependent on data – the more data you have, the better results you get. Google have driven this to a new level by embracing Cloud, Big Data and Data Exhaust to store every spoken or written search phrase entered into its systems. Using Big Data statistic searches, Google’s speech recognition can determine words based on its digital content.

Additional capability is delivered by Smart phones, which now have as much processing power as the mainframe machines of the ’90s. Coupled with high-bandwidth data connections to the cloud, remote servers can perform the heavy lifting required for both voice recognition and understanding spoken queries.

Using machine learning and statistical data-mining techniques, smart phones can now understand human speech. People now talk to their smart phones, asking to send email, search for directions or find information on the web – want to know more, ask Siri.

Speech is an exciting interface and can dramatically simplify interactions more than anything else. When using mobile applications, speech is the natural interface – typing will always prove to be frustrating and erroneous.

In a world where people are increasingly interacting with technology, the voice of the customer will be stored in the cloud. This data can then be accessed and analysed to provide new innovative services such as fraud detection and security biometrics to name but a few.

As an example, Sberbank the largest retail bank in Russia has utilised speech recognition in its ATMS for lie detection. By testing the customers responses to questions from a database of interrogation recording, Sberbank are able to ascertain when people are lying, dramatically improving their fraud detection rates.

For financial organisations, speech recognition is on a new and exciting trajectory. With a well established presence in call centers driving operational efficiency, the new technology wave for speech will see it become embedded with new emerging technologies such as Big Data and Cloud to create new operating models to drive greater product differentiation and customer value.

Today we can talk to computers, but very soon they will talk back.

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Big Data and the Challenge of Governance

In my previous post ( I disused that challenges of extracting value from Big Data using new forms of competitive advantage, such as dark data and data exhaust. In this post I am going to discuss the challenge of governance for Big Data.

Many organisations believe that Big Data is somehow different and is not applicable to the same degree of governance rigour. This couldn’t be further from the truth. Big Data has the same hallmarks as small data when it comes to governance. The key differentiator is the volume, velocity, variety and volatility of information being processed.

Competing On Insight
The search giant Google was one of the pioneers in Big Data, as seen with the launch of their BigQuery analytics tool, an area that has now developed into an industry worth billions of dollars. Big Data provides the opportunity to develop new operating models and new products based on real time customisation and pricing.

Data As A Currency
With the new analytical tools comes the ability to aggregate data. Organisations can now combine an internal view of their customer with geo–spatial information, such as Foursquare and Twitter, to generate targeted offers and promotions. Without a doubt, data is a new currency that can be traded and invested to drive customer engagement and product differentiation.

With this explosive growth of data and real time analytics comes greater responsibility to balance the need for knowledge with the right of the individual. Data by its very nature is contextual. When an individual shares information on Facebook, they are sharing stories, news, and information with their trusted network. Big Data can identify patterns with unintended consequences when aggregating data.

A recent and prominent example, from the US superstore Target, was when a man discovered his teenage daughter was pregnant because coupons for baby food and clothing were arriving at his address from the store. The daughter, who had not told her father she was pregnant, had been identified by a data system that looked for pregnancy patterns in purchase behaviour.

With Big Data we are entering a new era of ethical convention and challenge. The relationship between the social citizen, the customer and the organisation is changing. Big Data can pick up on trends and insight with unintended consequences.

With Big Data comes greater opportunity to increase customer engagement and competitive advantage. At the same time this represents a significant moral and ethical hazard for the uninitiated. Organisations need to be able to compete with greater responsibility and balance the need of the individual and customer versus the right to access data as a new currency.

In 2006, AOL released anonymous search results in to the public domain. Unknown to AOL, this information was re-engineered by an individual who was able to make it no longer anonymous, thereby identifying the original search details. This information was then aggregated by the New York Police department, across their own photo records and face recognition software, to arrest an individual for attempted murder. In this instance, the New York Police department got their man but with these new tools, comes a new ethical dilema. There is a moral responsibility to ensure that there is clear definition of how the data will be used and potentially aggregated.

The customer’s expectations of trust has to be managed alongside privacy laws and regulation. When the data is collected, if the customer agrees for his information to be used only internally to the organisation, aggregating the internal view of the customer with his facebook profile is clearly a violation of privacy rights, as was illustrated in the Target example above.The sensitive nature of information is critical for all organisations.

In my experience, that are 7 key steps than need to be managed for effective governance of Big Data :

1. Define the business stakeholders and business benefits for Big Data
Make Big Data a business driven initiative. Define who is responsible for owning and maintaining the data

2. Define the organisational structure, scope and governance model for Big Data
How much and what type of data can the organisation consume from the clients public profile? Has the customer agreed to the aggregation of their internal and external profiles ?

3. Define Big Data custodians for both internal and external data
Who owns the internal and external view of the customer within the organisation ?

4. Definite risk factors and controls for Bug Data governance
What are the new laws, regulations & privacy standards for data aggregation?

5. Document policy and procedures for Big Data
How is the data maintained and audited to ensure integrity and compliance?

6. Define quality management policies
How is the data managed and maintained for accuracy and integrity?

7. Information Security and Privacy
How does Big Data change the concept of information as a corporate asset? How do all these Big Data technologies relate to our current IT infrastructure?

Only by implementing a clear and structured data charter, with an increased level of rigour and due diligence, can an organisation be confident that it has the correct level of governance.

To Conclude
Big Data brings a new era of moral hazard and commercial ethics. Against a backdrop of phenomenal scale and power to uncover commercial insights, Big Data can generate unintended consequences without the correct level of stewardship and governance.

Organisations need to revise customer interaction and data charters on how they aggregate the internal view of the customer with information available in social and public domains.

As Big Data becomes increasingly important, and new disparate data sets are shared and aggregated, the stewardship of how this information is consumed and aggregated will be central to both data privacy and how an organisation maintains its trust and integrity with its customers.

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Big Data – Extracting Value

 “Most companies only capitalise on 5% of their in-house data”

This was the message at the leading Big Data Summit 2012. In a presentation from Forrester Research it was identified that most financial organisations are unable to extract and exploit the true value from the vast amounts of information they hold.

Big Data is often used to describe the vast data sets that are too large and too complex to be processed by conventional means. In a previous post (, I defined Big Data as

Volume – from hundreds of terabytes to petabytes, where a petabyte is equivalent to 500 billion pages of standard printed text.

Velocity – up to near real time sub second delivery

Variety – including both structured and unstructured data

Volatility – hundreds of new data sources coming online from new apps, web services and social networks

The key focus for Big Data is Value in order to drive new competitive insights.

Value – the opportunity to define new operating models and products based on customer insight and intelligence

In this post we will discuss how to increase value from Big Data to enable companies to utilise more that 5% of their data assets and directly increase customer insight, intelligence and information to drive competitive advantage.

Extracting Value
At the Big Data Summit 2012, Holger Kisker (Principal Analyst, Forrester) reported that companies are unable to extract value and exploit commercial insight from the vast amounts of data they hold on products, customers, research and market trends.

Looking at this in more detail, the volume of data available is truly staggering and is measured in Zeta bytes (1021 , bytes) as illustrated in the following schematic.

Source: Sept 20, 2011, “Understanding The Business Intelligence Growth Opportunity” Forrester report

The vast majority of information available to companies is historical data. This comprises of the traditional reporting, such as structured databases and reports, as well as the unstructured data that is available both internally and external to the organisation in the form of emails, phone calls and online content. This historical information far exceeds the information being generated now and in the future.

To be successful in this new data world, financial institutions have to realise that they are in the data business and that data is their biggest asset.

Dark Data
The vast majority of information is dark data – this is data that is either under-utilised or mothballed.

In a world where we are over run by dark data, whether it is social, machine data or location data, the ability to extract value and develop new products and operating models based on deep customer insight and intelligence represents a new form of competitive advantage.

Value is focused on forecasting, trend spotting, developing new products or detecting fraud in real time. Underpinning this is the ability to build a 720◦ view of your customer.

The 720◦ Customer

To capitalise on company data, organisations need to extend the internal customer view to include an external perspective. Specifically, organisations need to build a 720◦ view of their customers to unify the internal view with the client’s external social and influencing network, such as Facebook and Twitter.

As an example, British Airways is delivering a targeted and personal touch through its “Know Me” programme by researching passengers and building a unified view of the customer. The “Know Me” programme will use Google images to find pictures of passengers so that staff can welcome them by name as they arrive at the terminal or plane. This is the kind of individual service, providing a unique and personal experience, that we all aspire to receive.

By building a 720◦ view of their customer, companies such as British Airways will drive new opportunities for revenue uplift through mass customisation, offering benefits such as individual prices and targeted offerings based on predicted behaviours and location based services.

Data Exhaust

An exciting by product of Big Data is Data Exhaust. This is the unstructured information that is a by-product of the online activities.

Google applies the principle of data exhaust to many of its services. In a world where Microsoft spent several million dollars developing a spell checker, Google developed a leading spell checker , in every language, based on the mis-spellings typed into its search engine. The Google spell checker was developed on the by product of Data Exhaust from its online search engine.

Collecting and analyzing data exhaust can provide valuable commercial insight into the behaviour, actions and aspirations of your clients. Re-using data exhaust to improve a service or create a new product will be a new form of competitive advantage for those organisations embracing Big Data.

The debate on Big Data is often focused on the underlying data volumes or the new innovative tools and techniques. As I’ve highlighted here, the real opportunity and critical success factor is VALUE – how to extract value and exploit the information to enable better informed decisions and strategic outcomes.

Only by pulling data together from different structured and unstructured sources and developing new ways of processing, such as the 720◦ Customer and Data Exhaust, can organisations successfully develop new seams of competitive advantage and harness the 95% of untapped Big Data resources.

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Financial Times Interview

The Financial Times have just published the video of  an interview taken when I was CIO Corporate Banking at RBS.

As part of a leading CIO Series, I was interviewed by Paul Taylor ( US Business Technology and Telecoms Editor, Financial Times ) for my views, insight and expertise on the post crisis rebuild of the financial services technology sector ( ).

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Top Key Skills Needed For Today’s CIOs (Part 4 )

In my previous posts on key skills for today’s CIO, I discussed Visionary & Strategic Leadership, Building High Performing Teams alongside Operational and Technical Excellence.

In the final post of this series, I will explain the principle of Detailed Product Leadership.

Detailed Product Leadership

Product Leadership is the concept of radically innovating products, markets and business models to deliver customer led innovation and competitive advantage. In other words, it’s all about becoming a trusted advisor to the business that is truly passionate about the client, its business, products and services.

Product Pioneer
To support this pioneering journey, IT is a critical enabler for both internally and externally focused innovation including re-inventing and repositioning products in the market place. In a world where credits & debits are highly commoditised, innovation has to focus on new products & services, such as digital wallets and cashless payments, through to social CRM and big data.

In today economy, this can only be achieved by conducting a product / service profitability analysis to capture customer desires, supply chain demand with emerging trends and marketing analysis, to reveal rich seams of undiscovered customer needs.

This wealth of information can be mined to reveal unmet needs and customer sentiment, leading to a radical innovation of products, process and business models.

CIOs that want to become true product pioneers will need to drive business strategy and innovation coupled with a deep customer understanding.

This will be achieved by focusing on:

  • Market Knowledge – being passionate about the business. Knowing the industry and the competitive environment.
  • Strategic Orientation – aligning the technology vision to meet both the short and longer term goals of the business.
  • Commercial Orientation – understanding the cash and capital requirements to drive both top line revenue growth and bottom line earrings.

Analytics & Dashboards
This can be supported by developing a culture of analytics to measure everything you can, including dynamic dashboards to generate real time insights up and down the value chain.

In my experience, this will lead to improved real time decisions based on improved analytics and business case monitoring to evaluate ‘best of breed’ v ‘best of need’ solutions to deliver an enhanced product proposition.

Detailed product leadership is focused on making things happen. It’s about becoming a trusted advisor to the business, to weave IT and business strategy together, to radically innovate products and markets to deliver a concrete value proposition to both the business and its customers.

In this series, I have discussed the top key skills that are needed for today’s CIO. In the current environment, things have to happen differently. To be successful, CIOs have to exceed and out perform in the 4 top key skills of :

  • Visionary & Strategic Leadership
  • Building High Performing Teams
  • Operational & Technical Excellence
  • Detailed Product Leadership

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Top Key Skills Needed For Today’s CIOs (Part 3)

As the third post in the series of “Top Key Skills Needed For Today’s CIO”, in this article I will be discussing how to drive value through Operational & Technical Excellence.

Operational & Technical Excellence
In the current economic climate, organisations are being increasingly forced to examine opportunities for cost compression and complexity reduction to drive business growth.

This can be achieved through a process of operational and technical excellence across technology and the wider business organisation.

Central to this is a clear understanding of the business dimensions through defined corporate goals and objectives. Only by looking at the business domain can the CIO identify wider issues, identify opportunities and resolve business challenges.

Increase Organisational Effectiveness
To drive enhanced real times decisions across the organisation, CIOs need to radically simplify business processes. This process simplification needs to be achieved from the point of view of the end customer as opposed to the business owner. It should focus on stream lined operations, industrialised processing and organisational effectiveness.

This will need to be achieved through a detailed focus on cost control alongside the rationalising, renewing and consolidating of application hardware portfolios. In parallel is modernisation and potential outsourcing of non critical IT functions.

Delivering value through operational and technical excellence requires an investment management approach.

Key to this is identifying and capturing key indicators and metrics to detail the investment story. This will include measuring all key indicators, both quantitative and qualitative, from return on investment through to total cost of ownership.

By using an investment management approach, as opposed to a typical Red/Amber/Green ‘RAG’ status, the CIO has the opportunity to map IT metrics onto business KPIs. The mapping of IT metrics will then be directly linked to strategic objectives and business outcomes.

Driving value from Operational & Technical Excellence requires a concrete value proposition for the organisation to drive top live revenue growth and bottom line earnings. Processes need to be reengineered to provide scale and elasticity centred on the customer proposition and benchmarked using investment management performance indicators.

In the next post, I will discuss Detailed Product Leadership.

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“Top 25 Social CIOs in the Fortune 250” Awards

Forbes the leading publication for the world’s business leaders (, provides real-time reporting and concise analysis for the global business community.

As part of a leadership feature on social business transformation, Ian was given the prestigious international award of number 4 in the ‘Top 25 Most Social CIOs in the Fortune 250’ (

Ian was recognised along with Oliver Bussman (Global CIO, SAP), Benjamin Fred (CIO, Google) and Abraham Galan (CIO, Pemex) as one of the leading global CIOs driving social business transformation from the Fortune 250.

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Top Key Skills Needed For Today’s CIOs (Part 2)

In my previous post “Top Skills Needed For Today’s CIO” I discussed Visionary & Strategic Leadership.

In this post I will be looking at the key CIO skills to Build High Performing Teams that are lean, agile and highly focused

Building High Performing Teams
To succeed in building a high performing team, there are a number of critical competencies that the CIO needs to develop across the technology organisation. These include

  1. Strong Customer Focus
  2. Commercial Orientation
  3. Team Motivation

1. Strong Customer Focus
In my experience, all high performing teams need to focus on treating the business as a true client and manage the technology organisation as a business.

This can only be achieved by generating energy and enthusiasm to understand the client’s business, their commercial drivers and pinch points through to the client’s products and supported services.

The technology organisation will need to be truly passionate about the organisation, its commercial drivers and cash flows. This includes demonstrating a deep understanding of how the financials for IT work, the costs / benefits of the IT investment and how this compares with other investment opportunities.

Only by building inspired client relationships with the business can the technology organisation become a true trusted advisor and exceed customer’s expectations in today’s fast moving, global market place.

2. Commercial Orientation
Strong commercial orientation is critical for all leading technology organisations and is often overlooked.

Only by understanding what the commercial hot buttons are, coupled with a detailed understanding of the technology landscape can you become a valued and respected trusted advisor to the business.

Direction should be focused on inspired conversations with the business and the commercial insight to recognise that you understand their business, the products they trade and the positive impact that technology investment will have on top line revenue growth and bottom line earnings.

Only by being on top of your game both commercially and technically, can the IT organisation build inspired relationships as a trusted advisor that are critical to the success of the business today, tomorrow and in the future.

3. Team Motivation
Creating a high performing team requires an environment where all members of the team feel valued and that their contribution is recognised.

Staff need to have the opportunity to discuss the bigger picture. Key to this is regular and timely briefings to discuss the commercial picture, the strategic drivers and the business value that the technology organisation will deliver. This can be achieved through town halls, leadership briefings and deep dives.

Deep dives gives the individual the opportunity to showcase their expertise and increase the overall knowledge of the team.

For the individual, there needs to be a clear value proposition – what are their personal drivers and how can the organisation meet those needs both in the short and longer term. This is underpinned from recruitment – from hiring for attitude and training for skills, through to an established talent & performance management programme that nutures and develops expertise across the technology organsaiton.

Building a high performing team requires a new value propostion from the technology organsaiton.

This need to be driven by strong customer focus, detailed commercial orientation and exceptional motivation to leverage the true value of technology and its people. This in turn drives business strategy, innovation and competitve advantage.

I look forward to your comments on Building High Performing Teams. In the next post I will discuss Operational & Technical Excellence.

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Top Key Skills Needed For Today’s CIOs (Part 1)

In today’s business landscape CEOs are increasingly focused on top line revenue growth and bottom line earnings along with increased pressure to execute at speed and scale. Business executives are now looking to their CIOs to drive growth and competitive advantage.

To succeed and outperform in this environment, today’s CIO need a number of unique skills:-

  1. Visionary & Strategic Leadership
  2. Building High Performing Teams that are lean, agile and highly focused
  3. Operational & Technical Excellence
  4. Detailed Product Leadership

In the first of a series of posts on key skills for today’s CIOs, we discuss Visionary & Strategic Leadership.

1. Visionary & Strategic Leadership
From talking with many CEOs, all organisations have the same challenges. Their capabilities overlap through growth and acquisition resulting in process / service duplication driving up costs.  In addition, after successive waves of cost rationalisation, companies are struggling to find the next big efficiency.

Companies are seeking CIOs that can deliver competitive advantage through increased business alignment, strategic innovation along with increased business skills.

Increase Business Alignment
For organisations to succeed in today’s market place, the focus needs to be on Intelligent Growth comprising of:

(i) Customer experience innovation

(ii) Permanent cost & capital management

(iii) Streamline operations and increase organisation’s effectiveness

Technology and business strategy needs to be aligned and woven together to meet both the short term and longer term objectives of the business.

Strategist and Innovator
As a strategist and innovator, CIOs have carte blanche authority to develop processes, markets, departments and structures to generate competitive advantage. The CIOs that are visionaries and risk takers will benefit most from current opportunities.

CIOs will need to look outside of the normal technology domain and focus on products, markets and business models.

Several key areas include cost and complexity reduction, modernisation of non critical IT functions along with product and process simplification to drive improved real time decisions.

Business Skills
Businesses are increasingly looking to their CIO to drive growth and competitive advantage. Technology leaders are required to possess business skill sets in order to transform the technology organisation and change the technology / business industry value chain.

This can be achieved through inspired relationships by creating new and stronger connections with end customers and key stakeholders in the value chain.

CIOs will need to communicate IT performance in business relevant language using investment terminology to define the value contribution to deliver a concrete proposition for the organisation.

In today’s demanding landscape, CIOs need to be bolder, leaner and more focused.  Only by increasing business alignment and driving strategic innovation, coupled with new business skillsets, can they exploit leaner, more focused opportunities up and down the value chain.

In my next post I will look at high performing teams for a lean, agile and highly focused technology organisation. For now, take the time to review the visionary & strategic leadership aptitude for your own organisation and let me know your comments.

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Big Data – The Next Frontier

Big Data will be the next frontier for innovation, competition and productivity according to a recent report from McKinsey (

According to McKinsey :

30 billion pieces of data are shared on facebook every month

40% growth in global data, year on year

And by 2013 :

14% of business intelligence (BI) deployments will combine BI, collaboration and social media in to decision making environments.

33% of business intelligence functionality will be consumed via hand held devices

Big Data describes the data sets that simply cannot be tackled using traditional database and business intelligence tools.  In my opinion, Big Data is best described by a number of key attributes :–

Volume – from hundreds of terabytes to petabytes, where a petabyte is equivalent to 500 billion pages of standard printed text.

Velocity – up to near real time sub second delivery

Variety –  including both structured and unstructured data

Volatility – hundreds of new data sources coming online from new apps, web services and social networks

Data Strategy
To do Big Data well there needs to be a combination of machine intelligence and human insight. The vast amount of data involved is staggering – to sift, mine and identify the right information will require a fully integrated approach to managing both the product and data lifecycles for an organisation.

This will need to be built around a data management strategy that integrates Big Data into the front end of the innovation pipeline. This will involve a number of new alternative delivery models such as a new breed of analytical applications, using in memory capabilities to add scale and computation speed.

The benefits for Big Data are immense, from identifying the profitability of  customers, products and channels, through to mining customer needs desires and sentiment.

The more intelligence you have on your customers from Big Data, the greater insight you can apply to new products and services, driving greater impact on revenues, margin and market share.

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