Defence aspires to achieve Information Advantage. Microsoft’s TechIntensity approach delivers it.

TechIntensity is a Microsoft concept based on a few simple principles to help organisations succeed using digital capabilities and digital transformation. Tempo is a significant concept in Defence, where it provides military advantage in relation to adversaries. TechIntensity is to Digital Transformation what Tempo is to Warfighting – it drives advantage in comparison to adversaries and competitors. The concept enables Defence to identify where it needs to concentrate digital transformation resources and where it can achieve the greatest information advantage.

Satya Nadella, Microsoft’s CEO, explained TechIntensity at the recent Future Decoded Event in London.

“Each of us has to do really two things: One is we need to make sure that we’re adopting the latest and greatest technology. And second, we’ve got to build our own digital capability. Irrespective of which industry you’re in, you’re a digital business and you’ve got to do both”

Microsoft uses a simple equation to explain the concept: Technological Capabilities amplify Technological Adoption. It contains, though, more insight than just the simple formula used to explain it:

TechIntensity = TechAdoption ^ TechCapabilities

There a four basic blocks to the concept:

1. Every organisation is a digital organisation
2. Innovation Advantage through World Compute
3. Domination of Artificial Intelligence
4. Speed of adoption provides advantage

Every Organisation is a Digital Organisation

It is hard to ignore the digital transformation of recent decades, yet the cultural change that has been introduced is far more profound than the technology that has been adopted. Indeed, the latest technology is probably only current for 18 months, and so organisations cannot rely simply on a new tool to provide advantage. It is those that adopt like digital organisations that are most successful, not those that just buy the latest digital tool.

Today, all organisations are digital organisations. Those that exploit this fact are most successful, especially when they realise that digital transformation is unique to their organisation. Companies cannot simply copy and paste another organisation’s technical adoption and capabilities to succeed, nor can they simply obtain the latest technology. A successful organisation understands its own issues and advantages, and how it evaluates, adopts and replaces capabilities within a broader digital culture.

Technical Adoption (how an organisation performs as a digital organisation) is the crucial component. The Technical Capabilities then amplify that adoption for better or worse.

Throwing faster and smarter tools at a slow and dumb process will just accelerate the inevitable failure. Throwing faster and smarter tools at a fast and smart process will amplify its performance.

Digital organisations evaluate, adopt and replace technology quicker and more efficiently than traditional organisations. This provides advantage over their competitors. Organisations that have long procurement cycles, complicated contracting mechanisms and disconnects between operations and development are those that will flounder. This is more than just automating process, it is about how Defence must become a digital organisation with a digital culture across its entire business, and not just in the sharp end of warfighting.

Default Cloud is the world’s computer

The concept of ubiquitous computing, hybrid clouds, connected intelligent edge devices and default cloud are anathema to many in defence. Microsoft has a core view that Cloud computing serves as the world’s computer which provides innovation advantage and pace over older on-premise or static solutions. Cloud is the enabler of digital transformation. Decisions to only implement on-premises networks and computing will involve paying an increasingly large innovation cost – innovation is faster on a global computer where ideas are created, shared and improved faster than isolated teams and networks.

Whilst Defence may last longer than many organisations due to its bulk and legacy, it will eventually collapse against cheaper and quicker innovation from cloud computing in the same way that the USSR centrally controlled markets could not compete with Western entrepreneurs and free markets. Defence must explain how its legacy systems and processes will drive digital pace of innovation and adoption across its entire business and, where it cannot articulate the better future, replace those systems and processes.

Amplification through Artificial Intelligence

Microsoft passionately believes in amplifying human ingenuity with artificial intelligence and it is AI that unlocks TechIntensity. AI provides the ability to improve business process, predict organisation needs and deliver innovative solutions at a faster pace. TechIntensity will be greatly amplified through adoption of Artificial Intelligence.

AI will change the pace of adoption, growing TechIntensity within those organisations that can implement and adopt it ahead of their competition. In Defence, most interest in AI has been around either decision support (especially in operational decision making) or on data analysis for intelligence insight. Yet it is still in the foothills of adoption and Defence has largely ignored the opportunities already implemented in manufacturing, financial service and health sectors. Defence must articulate its AI strategy to support the digital transformation required for information advantage.

Speed of Adoption provides Advantage

Organisations that adopt and adapt technical solutions for their own goals will survive for a while. Those organisations that adopt and adapt for their goals ahead of their competitors will succeed. It is possible in the Defence sector that global adoption will be slow and steady across all nations, allowing a marginal gain to have a slight advantage in comparison. This has, for most of history, been the natural order for Defence. Knights fight knights, soldiers shoot soldiers, tanks destroy tanks. Defence is often slow to adapt.

Yet It is also possible that a military organisation will increase its TechIntensity at such a rate that it gains a significant advantage. These revolutions have been well documented, whether longbows, trains, machine guns or tanks. Western militaries have also been obsessed with technology capabilities for decades, believing that technology alone will provide enough advantage against adversaries. Previous revolutions have shown that it is not Tech Capability that wins wars, but the TechIntensity based on Adoption amplified through Capability. Many nations deployed tanks before World War 2. Only Germany used them to amplify their Technical Adoption approach.

In the MOD’s view, information provides the possibility of advantage in the future. Yet it is also a partial adoption. There is talk of cultural transformation and information as a bedrock in the future of UK Defence, yet also concerns about how far information can be exploited and whether AI can be trusted to do more than assess data. It is a vision of hedged bets and cautious change that does not sit easily when viewed against the real-world changes across societies and industries.

TechIntensity is concept of advantage and tempo. It takes the digital transformation that has changed the world and shows that simply acquiring new technology is an ineffective strategy. Instead, it concentrates on how organisations act as digital entities across their entire business, understands that organisations need to adopt in their own way, and amplifies that adoption through evolving capabilities. It is a concept that explains how to achieve Information Advantage.

To realize the full benefits of AI, we’ll need to work together to find answers to these questions and create systems that people trust. Ultimately, for AI to be trustworthy, we believe that it must be “human-centred” – designed in a way that augments human ingenuity and capabilities – and that its development and deployment must be guided by ethical principles that are deeply rooted in timeless values.

At Microsoft, we believe that six principles should provide the foundation for the development and deployment of AI-powered solutions that will put humans at the centre:

• Fairness: When AI systems make decisions about medical treatment or employment, for example, they should make the same recommendations for everyone with similar symptoms or qualifications. To ensure fairness, we must understand how bias can affect AI systems. 
• Reliability: AI systems must be designed to operate within clear parameters and undergo rigorous testing to ensure that they respond safely to unanticipated situations and do not evolve in ways that are inconsistent with original expectations. People should play a critical role in making decisions about how and when AI systems are deployed.
• Privacy and security: Like other cloud technologies, AI systems must comply with privacy laws that regulate data collection, use and storage, and ensure that personal information is used in accordance with privacy standards and protected from theft. 
• Inclusiveness: AI solutions must address a broad range of human needs and experiences through inclusive design practices that anticipate potential barriers in products or environments that can unintentionally exclude people. 
• Transparency: As AI increasingly impacts people’s lives, we must provide contextual information about how AI systems operate so that people understand how decisions are made and can more easily identify potential bias, errors and unintended outcomes.
• Accountability: People who design and deploy AI systems must be accountable for how their systems operate. Accountability norms for AI should draw on the experience and practices of other areas, such as healthcare and privacy, and be observed both during system design and in an ongoing manner as systems operate in the world. 

Extracted from: https://news.microsoft.com/futurecomputed/

Originally Published 9 February 2018

Tactical Technologies of Interest at DSEI 2017

DSEI is the UK’s largest defence event and showcase for future battlespace technologies. Yet seasoned visitors regularly view similar equipment from similar vendors just re-painted in the latest colour scheme. So did anything stand out as different this time?

DSEI begins with a strategic conference, and the Land Conference was entirely devoted to Artificial Intelligence (AI), Autonomy and Robotics. Industry speakers highlighted the global impact of these technologies, whilst military speakers raised the challenges they would face when adopting and implementing these technologies at pace. Both sets of speaker agreed that the ability for defence procurement cycles to meet the anticipated pace of development was a major risk.

The stand out conference presentation was OxBotica’s driverless vehicles[1], with almost every presentation using their impressive videos. OxBotica, based in Oxford, deliver road and cross-country systems that use cameras rather than GPS for navigation purposes, allowing highly accurate manoeuvre in periods of radio jamming or denied spectrum operations. The UK is driving to be a global leader in this market, and UK Defence is a great ‘vehicle’ (though not driverless) to champion that cause.

BAE highlighted autonomy with a dancing performance of flying robots[2], a collection of Unmanned Aerial Vehicles (UAVs) performing regularly on their stand; changing formation, swapping positions or pirouetting in turn. Part programmed, part intelligent swarm, the display helped move the debate on from military people controlling robots to military robots controlling robots.

Research demonstrations have shown that intelligent swarms can fill network gaps and intelligently re-position to maintain connectivity. Seeing such a swarm perform on stage made many visitors realise that these seem, at last, to be tangible, rather than just research and marketing fictions. The Defence world needs to comprehend how this reality will impact users, networks and procurement.

It now seems inevitable that the retreat of personnel from the battlefield will be an enduring truth of the tactical battlespace

Other manufacturers highlighted a range of Unmanned Systems, and it now seems inevitable that the retreat of personnel from the battlefield will be an enduring truth of the tactical battle-space. Yet it is not the clever technologies or systems that caught the eye; instead, it is the user expectation that UAVs will be seen across the battlefield for all users at every level. UAVs have gone from “Where?” to “Everywhere!” in the blink of an eye.

If Defence struggles with implementing systems in a rapid manner (UAVs have been on the horizon for over 15 years), then it seems to be engaging better with innovation, at least in identifying the need to foster more innovative approaches. A MOD-led JHub Innovation area enthusiastically highlighted the ambition to take innovation seriously and implement better ways to access original ideas across Defence and wider communities.

Converting innovative ideas into actual capability is a problem that faces many industries, not just Defence. One example where it has worked is Frazer Nash’s Innovative Respirator Design, the result of a DSTL challenge to develop easily donned respirators without removing helmets. The result is a solution worn around the neck in a low profile format to reduce additional burden that can be quickly opened and sealed to the helmet for rapid protection. Not only is the result a great piece of innovation, UK DSTL are also actively seeking to exploit commercially the design and technologies.

Defence acquisition should be delivering soldier technologies on display today before the next event in September 2019

The theme linking all of these technologies is matching acquisition timescales with technology innovation and adoption. Whether established technologies like UAVs, innovative ideas like Frazer Nash’s respirator, or the next generation of BAE’s swarm robots; the biggest challenge facing them all is getting them into the hands of the users quickly. I have spoken about 18 month technology half-lives for the last decade, passionately explaining that users get the most from technology when it is still current.

In terms of DSEI cycles, this means defence acquisition should be delivering soldier technologies on display today before the next event in September 2019. That is a dramatic change in timescales, but one that matches the current pace of technology acquisition and adoption outside Defence.

This requires a far more radical and agile procurement approach, with more flexible and collaborative contracting models. In turn, such an approach needs high quality experience and trusted expertise to implement.

The goal of new technology in soldiers’ hands by 2019 may be too quick for some, but changing how technology is procured now is something that can and must be achieved.

[1] https://www.oxbotica.ai/

[2] http://www.baesystems.com/en/event/dsei-2017

Originally Published 6 October 2017

Wired Magazine recently published an article by General Richard Barrons on the need to share ideas on information warfare between Government and Industry, but is better sharing really the answer? Why are we still struggling in this area, when the alarm clock has been ringing so loudly for so long?

Time, Information, Cost.

Tic, Tic, Tic….

General Richard Barrons has passionately expressed his vision and fears about the future of conflict in his Warfare in the Information Age note (the WITIA note from December 2014) and now in Wired Magazine (link below if you are one of the few yet to read it).

Increased sharing of ideas around information warfare to protect the UK and its interests is needed, and UK Defence has been articulating its aspiration ever since WITIA was published. Doctrine and strategies are being developed, but right now we need clear focus to make that aspiration become reality. Time is ticking.

Industry and academia riding as the saviour of UK Defence is not going to address this challenge. It is a collective task, but there is not collective agreement. Some see that things must change, whilst some don’t grasp why they should disrupt the norm of platforms having primacy. It seems for some that long procurement times, large platforms and incremental cost creep are almost the natural order of defence. We are united on the need to change, but not the nature of that change.

We can however recognise three big challenges facing military users:

1. Wanting technology now, but accept procurement and adoption processes that deliver over many years. How do we reduce time to deliver?
2. Needing information advantage and manoeuvre, but accept information only as an enabler rather than the lifeblood of Operations. How do we put information first?
3. Exploit information capabilities, but accept savings on networks and capacity that restrict that exploitation. How do we spend more wisely?

We need not to adapt our thinking, but radically disrupt it. Tic. Tic. Tic…

Time needs to be targeted, and increased tempo introduced for acquiring and introducing capabilities. We can set two-year goals with agile delivery approaches rather than over estimated, optimistic life-cycles that anticipate delay. Focus on what must be achieved in two years, and ruthlessly drive towards that goal. We need to abandon the processes of delay, and introduce quicker, simpler ways for approval, acquisition and acceptance.

Information is the new blood of the battlefield, and it needs to be valued, understood, and placed at the heart of all operations and acquisitions. Information must come first. All programmes should explain how they contribute and exploit the information domain, far beyond just the appointment of a lead for an information line of development. All programmes should explain their information needs to provide maximum rather than minimal capability. We need to put Information Programmes above traditional capabilities to enable us to catch up, match and defeat our adversaries.

Costs need to be controlled and brought into perspective, based on this new emphasis on information first. Spending hundred million on single items yet only thousands on their information systems needed to exploit those platforms is not economical, proportionate or efficient. Information is so vital to success that we cannot scrimp on its provision. On the other, it offers significantly greater returns on investment, penny by penny, when compared to traditional defence expenditure and this opportunity must be seized.

Time, Information, Costs.

UK Defence has shown that it can improve in parts when delivering faster systems; or exploiting information; or controlling costs. For information age warfare, this must be done as a whole rather than in parts and we need to focus on how to unite these ideas. Without focus we will continue to aspire high and reach low.

Originally published 2 Nov 2017

Military adoption of COTS technologies face three significant challenges: exploiting technology at pace that matches commercial development; securely integrating any new technologies into an existing system; and ensuring that adoption does not risk operational success.

These three challenges cannot be faced in isolation as too often addressing one of these challenges often creates issues for the others to resolve.

The rapid exploitation of technology can be achieved through aggressively compressing acquisition timescales and by ensuring that the fundamental principles of the system architecture supports integration of new technologies.

Existing work on open architecture is beginning to show real benefit. This must start to address the security aspects for adoption of new technologies and open architectures should form the basis of integration for technology platforms with a standardised, scalable framework on which to introduce capabilities.

Implementing an “adopt quickly, replace imminently” solution based upon sound open guidance will deliver true operational gains with acceptable risks. The rapid adoption and replacement of technologies that fit within open principles and guidance, rather than attempting to purchase a single long-term solution, is a key change for Defence.

Defence is increasingly being asked to adopt systems in a more agile manner. That agility challenges traditional methods, including engineering approaches. Adoption of open architectures and systems is a proven way to implement agility with greater confidence.

Originally Published 1 November 2016

The recent announcement that Google’s Artificial Intelligence team has cracked the world’s most complex game, Go, has increased interest in military adoption[1]. However, there are high profile challenges facing military adoption of artificial intelligence, and the military has to address valid ethical concerns in a public way in order to encourage the right minds to be applied in the field without fear of public backlash or misuse of AI tools.

The military advantages of applying AI to military command and decision making are clear. Napoleon once claimed that the secret to his military success was not on the battlefield but in the days before battle where he would consider and plan every contingency or option. Then, during the battle, he could react quickly to challenges as he already had a plan in mind.

AI potentially offers decision makers the same advantage by quickly analysing a situation, creating possible outcomes and helping the decision maker to select the most beneficial option, approaches that are already developed for business uses[2]. This advantage is priceless for western militaries who focus on tempo and speed of decision making as their battle winning advantage. It also means that other nations, some without the same ethical basis, are seeing AI as a potential game changer. In this area, the military AI arms race has already started, and the US Department of Defence issued a directive back in 2012 that restricted autonomous and semi-autonomous weapons for ten years[3].

The first challenge, perhaps unexpectedly, is one of ethics rather than feasibility. Most leading companies in the AI space have established clear ethical rules regarding the use of their tools, partly to assuage concerns taken from films like Terminator about unconstrained AI causing future conflicts, and partly to reassure investors that their investments are sound.

In July 2015, over 3000 leading IT experts including Steve Wozniak, from Apple, Daniel Paul Gonzalez from IBM Watson[4], and Mustafa Suleyman from Google’s DeepMind[5], along with physicist Stephen Hawking, signed an open letter requesting that AI should not be used for autonomous weapons[6]. Their reasoning is that:

“Most AI researchers have no interest in building AI weapons — and do not want others to tarnish their field by doing so, potentially creating a major public backlash against AI that curtails its future societal benefits… Starting a military AI arms race is a bad idea, and should be prevented by a ban on offensive autonomous weapons beyond meaningful human control.”

Before using AI in the military field, these leading lights in the area, along with a sceptical public, need convincing that the technology is controlled and secure.

The second challenge is akin to cracking the Enigma code during World War Two at Bletchley Park. Nearly all of the geniuses in AI work outside the military and government domains, in the same way as the computer and mathematics geniuses worked outside the intelligence agencies before 1939[7]. It took a conflict of huge scale to drive nations to tap into the brilliant minds required to turn nascent computing into effective military tools. At the moment, there is no similar reason or reward for AI thinkers to focus on military rather than commercial or economic challenges, at least in the Western hemisphere.

Finally, most military commanders accept that AI can make more intelligent munitions yet there is a hesitance to adopt AI for decision making across elements of the chain of command until it has been more widely proven. Consequently, AI is perhaps a revolution that will first change society[8] before entering military use.

Yet military forces may not be able to wait to see society change with an AI arms race already beginning. Overcoming internal concerns that restrict military adoption should be quick to address when military decision makers realise the advantages that AI provides on the battlefield. However, those potential advantages cannot be realised without first addressing the ethical concerns in a public way and then encouraging the right minds to be applied in the field without fear of public backlash or misuse of their tools.

[1] Alphago: Using machine learning to master the ancient game of Go https://googleblog.blogspot.co.uk/2016/01/alphago-machine-learning-game-go.html

[2] Artifical Intelligence is almost ready for Business, Brad Power, Harvard Business Review March 2015 https://hbr.org/2015/03/artificial-intelligence-is-almost-ready-for-business

[3] Autonomy in Weapon Systems, US Department of Defence, 21 November 2012 http://www.dtic.mil/whs/directives/corres/pdf/300009p.pdf

[4] IBM Watson http://www.ibm.com/analytics/watson-analytics/?cm_mmc=search-gsn-_-branded-watson-term-_-watson%20analytics-Broad-_-UKI-WW-WA-mkt-oww

[5] Google DeepMind http://deepmind.com/

[6] AUTONOMOUS WEAPONS: AN OPEN LETTER FROM AI & ROBOTICS RESEARCHERS http://futureoflife.org/open-letter-autonomous-weapons/#signatories

[7] The Secret War: Spies, Codes and Guerrillas 1939–1945, Max Hastings, 10 Sep 2015 ISBN 9780008133023

[8] Artificial Intelligence is Changing the World, and Humankind must Adapt, Stephen Deangelis Wired Magazine, July 2014 http://www.wired.com/insights/2014/07/artificial-intelligence-changing-world-humankind-must-adapt/

Originally Published 23 February 2016

Five trends have emerged in today’s technology market that are revolutionising the future of mobile communications:

• the ownership of networks;
• understanding information utility;
• anticipating user needs;
• analysis of usage;
• personal predictions. 

Those same trends could have a revolutionary effect in the Tac CIS domain as armies struggle to win the information firefight.

In 2009, data traffic on mobile networks exceeded voice traffic for the first time. In 2014, mobile data traffic volume was 12x the volume of voice traffic, and total data volume for the first quarter of 2014 was larger than the total volume in 2011[1]. Data traffic is growing at 15% per year with no slow down whilst voice traffic has remained static since 2010. In short, the market has fundamentally changed.

However, network providers are struggling to reflect this change. In 2014, 85% of network traffic was data whilst it only accounted for 39% of revenue[2]. Most network models are still focused on volume of traffic – whether a call lasts one or ten minutes or a download is 1Mb or 1Gb is a relative price determined by the volume transferred. Companies like Vodafone have become providers of hardware (mostly at subsidised prices) and providers of bandwidth (charged at per-use rates). They are increasingly commodity suppliers with decreasing profit margins.

A large point of debate is that all content (voice or data) is equal. From many users’ perspectives content is not neutral. A voice call from a close relative is far more valuable than a random sales call. A downloaded video may be less valuable than accurately plotting a route around a major traffic jam during rush hour.

Users understand that content is not equal, even though they may be charged on an equal basis, and that the value of content depends on the context and time of consumption.

In a military perspective, most Tac CIS programmes still supply handset devices and bandwidth like a network provider or provide service management only as far as ensuring that the network is working. Like network providers, military programmes sometimes miss that the military user values content far higher than provision of bandwidth. The old model of price per byte is increasingly irrelevant for future communications, whether civilian or military.

The new model is a change that content providers in the entertainment sector have already recognised. Netflix has an exceptionally deep understanding of how its 60 million customers view and interact with their content[3].

When Netflix developed the series House of Cards it did so based on a detailed analysis of how the target user consumed content and their content preferences, combined with traditional film making skills. Netflix was able to examine its target audience viewing habits, how and where they viewed that content and, more importantly, what made the audience stop watching. This detailed analysis allowed David Fincher, the Director of House of Cards, to create a highly addictive series based on the type of content that the target audience wanted to view. Netflix is able to deliver highly addictive content by understanding its users’ preferences. It was able to develop ‘crack TV’ – highly addictive viewing that exactly matched the expectations and likes of the target audience[4].

Applying the same approach is highly desirable for military consumers, who require different information and content at different moments and for different purposes. For instance, military users require relevant information on enemy locations and local environment when planning an attack. During the advance they require regular updates to maintain current situational awareness about their own and enemy activities. At the point of attack, they most critically need the command to GO delivered with appropriate timeliness and emotion. Current military networks treat all these needs and their related content as equal, much the same as traditional mobile network providers.

Understanding how content is consumed on networks is critical. General Sir Rupert Smith wrote about The Utility of Force[5] in 2005 that politicians needed to understand what military force did that was useful before committing them to military operations to do those activities. The same argument, ten years later, can be applied to military information.

The military must understand the utility of information before making commitments on how it is provided or networked.

Applying an approach similar to Netflix, with active observation and awareness of the utilisation of content across its networks, would create this understanding. The result would allow network access based on an information utility basis rather than constrain access on a network capacity basis.

This model has been taken further by Amazon, who to a great extent pioneered the understanding of user value of information. Amazon realised that waiting for customers to find and purchase products was insufficiently effective, especially when operating on profit margins significantly lower than usual retail models. Amazon needed to encourage customers to buy their products on a regular and frequent basis to make a profitable margin. Traditional advertising that bulk pushed product listings to large volumes of customers did not translate into regular and frequent purchases.

Instead, Amazon realised that they had unrivalled access to the viewing and buying habits of its customers at an individual level. Amazon did not have to push bulk products at a high volume. Instead it could push specific products to individuals based on items that they have viewed or previously bought. Identifying those customers who bought product XXX often purchased product YYY allowed Amazon to significantly increase the uptake of advertised products. For a user, they felt that Amazon was selling relevant products that matched their interests and, significantly, that they had an interest to buy.

This predictability of purchase has encouraged Amazon in two mutually supporting directions. First, it has invested heavily in understanding and predicting individual customers’ preferences and needs. Amazon is able to predict customer behaviour and purchases to encourage sales.

The second direction is in storing and analysing customer data. Purchase history is only one aspect of accurate consumer prediction. They require large volumes of user data and the capacity to analyse that data quickly and cheaper. This brought Amazon into the Cloud Computing arena in a massive manner. In 2014, Gartner estimated that Amazon accounted for 83% of the cloud computing infrastructure market. Amazon have realised that the value of information is not just in predicting and meeting customer behaviour but also in hosting and analysing that behaviour on a massive scale. Amazon now provides those same cloud services to the CIA and 16 other US Intelligence Agencies[6].

Amazon dominates the market by providing detailed user analyse that is valuable and affordable with massive data processing conducted quickly and cheaply. Traditional military CIS has argued that their volume of data is too large to comprehend. In comparison to the volumes processed by Amazon, their demand is incredibly small and the Tac CIS environment even smaller. The secure storage, analysis and utilisation of Tac CIS information is a viable possibility today. The first step is allowing access to that information.

A competitor to Amazon in the cloud infrastructure market is Google who, like Amazon, entered the market initially to meet its own needs and then started to meet other organisations’ requirements as a result. Google initially specialised in user search as a way to sell advertising, although unlike Amazon they push individualised advertising from different organisations. Google’s approach to advertising was to target massive volumes of customers with highly targeted and effective messages, which has resulted in it dominating the advertising market[7].

Google initially analysed both the internet (the content that was being provided) and the user (the content that they wanted). At a simple level, they then matched the two together. In 2006, Google and Apple were collaborating over a new smartphone that would provide unrivalled access to the internet. Shortly after the launch of the iPhone in 2007, Google broke away from the initiative and began developing its own device, much to the annoyance of Apple’s boss, Steve Jobs[8]. Both Apple and Google realised that the device and its adoption of applications would revolutionise the way users consumed the internet. Google, more so than Apple, also realised that the new device provides unrivalled access to user data and preferences.

Google’s Android devices have swamped the market and have provided Google with incredible access to users’ consumption habits. As is well known, Apple’s App Store (and Google’s own version) has pushed billions of apps to customers[9] and nearly every interaction with those apps is recorded and analysed by the app developer and Google or Apple. Both Google and Apple have taken customer awareness to new levels by tracking users, locations and usage throughout the day.

The Apple model is based on a constant awareness of user activity, location and interactions whenever a user opens an app, interacts with the app or uses its content. It is the same model on a larger scale as that adopted by Netflix, with each app an unrelated activity or interaction.

Google is now pushing a new generation of user awareness and utility. Google Now takes a user’s most utilised apps and pushes relevant information to the user without the necessity of opening the app. It allows Google to read a user’s calendar, analyse a location mentioned in an appointment, determine the user’s current location, look up traffic conditions and prompt, without request, a reminder to the user to leave now in order to arrive on time. Google Now is a tool that anticipates needs[10] by taking Amazon’s predictability models, mixing it with Netflix’s consumption approach and adding Apple’s user awareness. Rather than open apps, Google Now acts in the middle and accesses content on behalf of users with incredible accuracy.

The iPhone model of user awareness was invented in 2006 yet still has relevance in today’s Tac CIS environment. However, Tac CIS is an environment currently constrained by bandwidth and with a need to minimise the cognitive burdens on users. In that environment, Google Now’s model of predicting and pushing information from across applications and sources has even more relevance and utility. The approach could potentially track a user’s location, compare it to the current plan, predict likely time of arrival, update the plan based on that arrival time and inform other units without user interaction. Some military users may baulk at such an all informed approach that doesn’t depend upon verbal updates, yet most military users ask for technology to reduce their information burden, which is exactly what anticipating user need achieves.

This model has also pushed Google into a new direction, encouraging it to become a network provider. Google is now providing networks for its customers because it realised that the value to its business is in understanding how customers consume content and information. This allows Google even greater awareness of user consumption. Google Fiber[11] provides cheap and high speed access in multiple US cities to encourage even more information usage and, in turn, even greater utility awareness by Google. Projects like Google Loon[12] have been started to employ a global network of high-altitude balloons to connect people in rural and remote access, reaching the two thirds of the global population without internet access. Google has realised that the value is not in the network but in the utility and consumption. Owning the network increases their awareness of this valuable information.

This brings the debate full circle. Military users can follow these examples and re-examine where the true utility and value lies within the military domain. Rather than adopting the network model pioneered in the 1990s that is now hindering mobile network providers, military providers should follow the Google and Netflix direction of travel.

Today’s military can focus on the utility and value of the information focussed on the consumption that is actually used within the systems.

The Military domain needs to predict and implement a model that exceeds expectations beyond the next ten years.

Introducing the capability and capacity to understand how and what their users are actually employing within the domain can be conducted today. Like Google and Amazon, they must examine ways to predict and push relevant information that matches their users’ needs and expectations. They need to consider owning networks that exceed user expectations rather than chasing fractional increases in capacity. Rather than adopt a model that is already ten years old, the Military domain needs to predict and implement a model that exceeds expectations beyond the next ten years.

Originally Published 11 June 2015

[1] Ericson Mobility Report 2014 http://www.ericsson.com/res/docs/2014/ericsson-mobility-report-june-2014.pdf

[2] Bloomberg 21 Mar 2012 Data: 85% of mobile traffic but 39% of revenue – what gives? http://www.bloomberg.com/bw/articles/2012-03-21/data-85-percent-of-mobile-traffic-but-39-percent-of-revenue-what-gives

[3] Forbes 20 Jan 2015 Netflix Soars on Subscriber Growth http://www.forbes.com/sites/laurengensler/2015/01/20/netflix-soars-on-subscriber-growth/

[4] The Guardian 23 Feb 2014 Netflix Gathers Detailed Viewer Data to Guide its Search for the Next Hit http://www.theguardian.com/media/2014/feb/23/netflix-viewer-data-house-of-cards

[5] The Utility of Force: The Art of War in the Modern World by General Sir Rupert Smith 29 Sep 2005 http://www.amazon.co.uk/The-Utility-Force-Modern-World/dp/0713998369

[6] The Atlantic 17Jul 2014 The Details About the CIA’s Deal with Amazon http://www.theatlantic.com/technology/archive/2014/07/the-details-about-the-cias-deal-with-amazon/374632/

[7] http://marketrealist.com/2015/01/evolution-online-advertising/

[8] PCMag 1 Dec 2014 Why Steve Jobs Went Thermonuclear Over Android http://uk.pcmag.com/mobile-operating-system/37891/opinion/why-steve-jobs-went-thermonuclear-over-android

[9] http://www.statista.com/statistics/263794/number-of-downloads-from-the-apple-app-store/

[10] Wired 17 March 2015 An Open Google Now is About to Make Android Super Smart http://www.wired.com/2015/03/open-google-now-make-android-super-smart/

[11] Google Fiber https://fiber.google.com/about/

[12] Google Loon http://www.google.com/loon/