Black Friday Comes Again

So it's that time of year where we all go collectively mad in the herd stampeded for bargains in the run up to christmas.

It's time to reflect that this sort of consumer fever is driven by mobile users and that the statistics are quite incredible for sales and year on year growth.

I know that not every business is involved in direct sales to consumers or that every market in the world is dominated by Christmas. However, many businesses have spikes in activity driven by certain times of the year. Local religious holidays are only one example. In the UK, the number plate registration scheme changes the primay letter on the number plate at fixed times in the year. This triggers not only discounts on cars with the previous period's plates, but also car loans and insurance renewals. Summer time often drives spikes in behaviour around drinks and ice cream sales, and school holidays drives resort bookings for travel in many parts of the world.

The important issue is that sales are increasingly being forced down the mobile access route and businesses need to plan for capacity spikes. This is great news if they are running on cloud platforms, but they should still be running planning sessions and exercises to ensure that they can scale. also they need to look at the back office and operational processes of their businesses to ensure that they can fulfil sales quickly, accurately and efficiently with minimal errors. As many digital businesses only work if they have rock solid operations in the "bricks and mortar" world.

Fundamental to this is the customer experience on digital platforms, IoT type instrumentation throughout the fulfilment process (with real time BI to monitor the situation for load, capacity and bottlenecks) and proven scalability, as there often are little niggles in scaling up cloud infrastructure in a responsive manner.

In the end, there needs to be a contingency plan to deal with SNAFUs such as problems with cloud platforms, which occassionally occur and some planning to deal with the types of security vulnerability which can occur when people, processes and systems are stressed by volume.

So balck Friday (or its equivalent) should be included as a major scenario for evaluation in any business's contingency planning.

What Does It take to be Agile?

There's a lot of discussion in many fora about the meaning of Agile, Agile Leadership and Agile Business, with some pundits even saying that "Agile is dead!" Inevitably many authors feel the need to go back to the Agile Manifesto and quote its principles. However, I feel that they get it wrong.

I have always had problems with the Agile Manifesto. Not because it was not a good thing or a great call to arms, but because, at its core, it just focused on 20% of any project or development activity. This really goes back to how it evolved as the shared set of principles that a dozen different groups found that they could agree upon and the fact that the lowest common denominator was the act of programming.

Just to illustrate the point, if you want to develop a mobile app and ask a man in a garret who specialises in these things, he will probably quote you somewhere around £20K for a simple app. By the time you have run through the whole project and costed all the effort which goes into the development, it will probably cost you around £100K to £120K in its entirety, because you need to go through the activities of planning, budgeting, researching, defining and agreeing requirements, workshops with users or customers, coding, demonstrations, testing, configuration management and publishing to get there, with some overhead for project management and development sourcing (even if this is internally developed).

The Agile Manifesto left out a lot of critical assumptions, such as some analysis is required to get to scope and a prioritised list of requirements. Standards and an architecture are mysteriously deemed to exist so that the developers can use them. Testing and implementation are miraculous things which just happen because working code has been delivered.

If you go into the real world, one of the biggest bottlenecks in delivering projects and products is Financial Approval. Often this has nothing to do with the business case, but more to do with internal organisational politics and the competition for investment funds. If governance is not well aligned to clear and explicit strategy, and the senior management of an organisation don't work well as a team in prioritising investments to deliver strategy and to preserve existing value, then this act can take longer than the actual project. So it was good to see Daniel Lambert's blog on strategy and architecture, discussing its need for success with Agile.

The Agile Business Manifesto is also an interesting document, although to my mind still a bit clunky and lacking focus on Quality, Value and Strict Scope Control (e.g. via MVP concepts). I also think that it is weak around Cultural orientation towards Innovation, Design Thinking and aligning Risk Appetite with Value. The principle around Strategy does not quite get the message across either. You need grand visions and hypotheses about how you will change the rules of your market, but then you need "proximate goals" or deliverable baby steps to address them with constant revalidation. Yet again there is the mistake of forgetting about data as well as informed decision making. Probably this is why awareness of the Manifesto is still low.

So we still need a better model and definition of Agile Businesses. Simply put, an Agile Business Focuses on Strategic Value and Quality, moving quickly and constantly to deliver ever increasing value. In doing this, it adopts an integrated team approach, encourages experimentation, prototypes and feed back, and analyses performance and perception data to fine tune delivery and plans. It never stands still, stops adapting or restlessly looking for new ways to improve value. It exercises a strong moral compass and attunes risk appetite to strategic delivery, innovation and optimal performance. It learns from experience, but also looks outwards for new ideas, inspiration and to understand trends.

Well that's my opinion anyway.

DevOps and AI means that Lean Data has another Principle

In an earlier post I expounded on the principles of Lean Data:

• Organisations know what data they hold and manage;
• Data is classified according to subject area and criticality;
• Only the minimum data necessary to Add Value to the business is held;
• Data replication is kept to the minimum level necessary to optimise business performance;
• Data Value is determined by its utility in Serving the Customer, Supporting Essential Capability, Protecting the Organisation, Providing Insight for Business Decision Making.

I also covered Data Portfolio Management. However, what I missed was the emerging issues around database management systems and Machine Learning. It appears that as people start to scale their Lean efforts (Strategic Alignment, Design Thinking, Agile & DevOps) they are beginning to realise that this includes data too.

What becomes increasingly important is having a handle on configuration management over data base design (i.e. schemas) and data sets themselves, ensuring that it is co-ordinated with code configuration management and integration across multiple deployments. This should have been implicit, but apparently it was not.

Therefore I suggest adding the principle that:

• Data configuration management of schemas, test data conditions and machine learning training data is co-ordinated with applications and code configuration management.

Another Week In AI & Machine Learning

Driveless

So the hot news this week is that people keep crashing into driverless cars. Wired magazine discusses the issue that the way in which the current generation of prototypes being driven on America's roads are experiencing a high level of accidents, apparently because they don't behave is the same way that ones driven by humans do. 86% of collisions in California this year have been due to being rearended or side wiped! Autonomous cars appear to be over cautious and annoy human drivers, not only by stopping unexpectedly but also because they are over compliant with the letter of the law in interpreting situations. So why don't they have signs on the car, just like a learner does to warn drivers that they need to keep clear? It's a pretty similar situation and people do tend to steer as clear as practicable from learners who they know to be unpredictable.

AWS Capability Continues to Grow

AWS also held its AWS Innovate Online Conference. In his "state of the nation" talk, Boaz Ziniman outline current capabilities available Off the Cloud (OTC) rather than Off the Shelf (OTS). Basically, AWS still provides impressive capabilities which allow a developer, data scientist or organisation to just start using AI and scale rapidly. Though they have been adding to this capability with impressively powerful capabilities around visual recognition and voice processing as well as bundled environments which are pretty much deploy and go. this is very liberating, because it provides a readily used Pay as You Go (PAYG) capability, which avoids much of the traditional issues of continuously having to research, select, implement, integrate and tune the suite of tools and infrastructure needed, as well as continuously returning to CAPEX approval and purchase processes for scaling to deal with increasing volumes of performance issues. 

There's a caveat though. Some of the capabilities, e.g. recognising a face in a crowd, which may be useful for security solutions, might also be used as the tools for enforcing a police state or merciless pursuit by paparazzi. Enabling such massive AI at scale, will to some extent be another nail in the coffin of personal privacy.

Early Adopters Surge Ahead

Finally, MIT Sloan and Boston Consulting Group released a report "Artificial Intelligence in Business Gets Real" which surveyed the application of AI in business across the globe. Whilst there were the usual scare stories about China being ahead of the West in adoption and that the gap between pioneers and laggards is growing larger there were some interesting points. The Chinese are deploying to meet efficiency and cost needs. Everyone else is deploying, because AI helps them do more and there was a message that AI will not replace jobs, but it will change the nature of work and the skills needed.

The second key message, was to experiment with something simple and demonstrate the benefits, because business leaders who had seen AI in practice, get it and are prepared to invest more, to the point that AI is almost addictive in the way in which it influences investment appetite once a business has tried it.

The final message was really around AI at scale. If you are planning on building your  future business model around AI, then you need to plan, prioritise long term investments and to get effective data governance in place. This does not just mean establishing once source of the truth, with valid, complete and coherent data. It also means having a good handle on version control. Since, if multiple applications of AI depend on the same data, it needs to be synchronised to avoid unintended problems. So Lean Data practices are fundamental to adopting AI at scale.

Finally, it was interesting to hear how paranoid Chinese companies, adopting AI, are about cyber security. Protecting their data from competitors and the continuing availability of data and AI based solutions becomes increasingly important once a company's business model has evolved to adopt AI. So the principle "Cherish your Data" (see The Way of DAU) is key to successful exploitation.

Conclusion

Human issues, ethics and common sense remain central to AI adoption, an Agile mindset encourages adoption and Data Governance is a key enabler.

Look Outwards Look Inwards - What Does it Take to Innovate?

The Leadership Crisis In Innovation

Today's Digitalised Business Environment has caused a crisis in leadership within most large global organisations. Many CxOs have come to realise that they and their colleagues in their Senior Management Teams are part of the problem. Though some remain incredibly blind to this fact.

Why is it that business leaders actually inhibit their organisations' efforts to transform, digitalise and innovate? There are many possible answers to this question, though for American and European companies, one of the answers may be that the background of the leaders dose not predispose them towards innovation. Too many organisations are dominated by people with Accounting or Legal backgrounds and unfortunately these professions tend to lean towards conservatism, compliance and enforcement of rules, rather than trying to break the mould or implement business and cultural change.

Another possible answer is that most management teams don't actually function as teams. They are too often populated by people who are locked into functional siloes and turf wars. So whilst it would be simplistic and cruel to accuse them of all conforming to the often quoted idea that only selfish monomaniacs reach these positions, the environments in which they work often pushes them to behave a like they are. This makes it difficult to build the collaborative, innovative and risk taking culture needed to survive and grow in the new digital market place. 

So various people have been researching what it takes to become an Innovative Leader. See HBR and the Conference Board.

A Model Of the Innovator as Leader

The diagram below summarises the findings of a couple of pieces of research and the author's own experience. So it may not be perfect, but it at least represents some contemporary thinking on the subject and, hopefully, is useful.

Whilst it may be too simplistic to state that an innovative mindset requires a leader to look both outwards and inwards, this does underpin a lot of what is needed. In the model, VALUE, CURIOSITY and CONSTRAINTS interact in an almost chicken or egg situation (which came first?). A lot depends upon context and situation as to which is the starting place but a sense of each is crucial to an Innovator. 

VALUE is key because understanding what is valuable to your organisation and its customers (or other stakeholders if it is a Not for Profit one). Almost everything that an organisation does, should be aligned to optimising value, i.e. growing, preserving or protecting it. This includes innovation. So it is fundamental to understand what value means to he organisation and to its customers. Of course if a leader is thinking about starting a new enterprise, then some opportunity identification may be required first.

Understanding the CONSTRAINTS that an organisation operates under and what currently dictates market behaviour in its industry or sector is also fundamental, because this drives the Why questions? Why do we do things this way? why do customers behave like that? why do we not do this. Why are the constraints there and why don't we do things differently? (The why questions are sometimes called the 5 whys or 7 whys and basically, is a process of asking why enough times to get to the root of current behaviour) which then leads to What if questions such as What if this constraint did not exist? what would happen if we did this differently? etc. which lead to some theories about what works now and what would work in the future if the rules were changed, as well as some options for how to make these changes actually happen, which are postulates about how to disrupt the market place and are sometimes called BIG RULES.

CURIOSITY comes in from the other angle of observing what happens in the market place and asking why people do things. It also involves consciously looking outwards into different industries and disciplines through networking, attending industry events and carrying out research to see how they tackle different problems and then thinking about what lessons can be applied to your industry or even would spur new products or a startup business. It has been observed that many innovators are T shaped, as opposed to I shaped. I shaped people, only think about their discipline and nothing else. T shaped people, whilst having deep knowledge in their own area, also exhibit curiosity about understanding wider practices outside their specialism and applying them in a joined up manner. Curiosity identifies opportunities and asks why as well as what value can be derived from change.

These 3 themes of Understanding Value, Reviewing Constraints and Curiosity lead to the development of Vision. However, in most cases it requires an energised team to deliver a vision and successful innovative leaders involve the team in building a SHARED VISION of how things could be. This is an essential step in TEAM BUILDING as it helps motivate the team and encourages it to amplify any innovative efforts. Though a complementary aspect of Innovators is speed. Getting to market with an innovation, delivers most value if an enterprise is either first or second to market with a well targeted product. Hence VELOCITY of delivery is important, though it needs to be tempered with actually meeting a real customer need and being reliably and economically deliverable. This leads to the use of EXPERIMENTATION to test out the understanding of these needs as well as what actually works, and may involve exploration of OPTIONs to optimise the product. VELOCITY is also re-inforced by agreeing mutual stretch targets with the product delivery team. Note, the term mutual is important, as this is part of sharing and building trust. If the team buys into the targets, then trust and openness are more likely to be encouraged, leading to better team performance.

Other aspects of TEAM BUILDING and successful product development include DIVERSITY of the team and fostering an information based culture of decision making. Diversity in the actual structure of the team involves not only building a multi-functional team involving the internal disciplines needed to design, develop, deliver and market the product, but also where practicable a customer element. It also may include multi-cultural, multi-age aspects to encourage creative vitality by encouraging multi faceted view points within the product development process.

Adopting an Information based approach, means that the team must be INFORMATION RICH. Where it does not have information to support its decisions, experiments, trails, prototypes or other research should be conducted and the knowledge gained should be readily shared to support both effective and informed decision making, but also foster trust and understanding within the team. Though sometimes it has to be recognised that it may not be practicable to collect data before a product is launched. In this case, the team may have to either build features into the product which collect the data, supporting future product iterations, or use other means such as agile marketing to test hypotheses.

The last bricks in the model are SIMPLICITY and SYSTEMS THINKING. Taking an end-to-end view of how a product is delivered, enables the product team to anticipate likely problems as well as analyse operational performance and customer experience during delivery, so that continuous incremental improvements can be built into the product, refining its capabilities and delivery. SIMPLICITY, is a principle that should be applied as far as practicable. The product itself should be made as simple as practicable to deliver the value required by the customer. The delivery processes should be kept simple too, ensuring that activity is concerned with delivering value or experience. If complexity has to be increased to add value, e.g. by operating in multiple markets, then the team should look to see what else can be simplified. 

Conclusion

A leader needs his or her team to perform, because the leader can not do all the innovation him (her) self. The Team will only work if it is empowered, informed and enthused. so innovative leaders can set the context and the challenge, ensure that their teams are well informed, but also challenge them on value and pace. However, this does mean avoiding death marches, mountains of red tape and punishing the innocent, when things don't go as planned. The old ways have to die.

Digital Revolution for the Hospitality Industry?

How would Digital affect a traditional industry such as the hotel business? Well there's certainly potential when looking at what happens today and it goes beyond just a clean up of the myriad of decrepit and unintegrated applications used today.

Starting with the first point in the Customer Journey Map, selecting a hotel, most hotels have their own website and are marketed through a number of web sites or via companies who have block booked groups of rooms within a hotel. (These websites and companies are often referred to as OTAs or on-line travel agents). At least one company, XcelTrip, is deploying Etherium Blockchain to disintermediate the middle men and provide hotels with a greater throw weight, whilst retaining a larger share of revenue for themselves, via a Distributed Travel Environment (DTE). 

Also, Virtual Reality offers a much improved way to experience what the hotel is like before you get there so, not only can you understand what the room and facilities are like, you can also see what the view is like and understand the location in which you would be staying. This should be a great draw, especially for premium hotels offering on site experience or prime locations as a special feature.

Secondly the arrival and process can be greatly improved, especially for frequent travellers and participants in hotel loyalty schemes. If the hotel room has been booked and assigned, there really is no reason for someone to queue at a desk to receive a key. Payment details and identification (e.g. photo or passport) details should already have been captured as part of booking or from stored information within the loyalty scheme database. So it should be more than easy to provide the room details and an access code via text, email or an app used by loyalty scheme members. In this case a traveller can go straight to his or her room, unless a porter is needed. Any final identity checks or validations could easily be carried out by facial recognition as the traveller enters the room.

IoT and the current generation of home automation technology show how much the room iteself can be automated from smart locks, through smart controls for HVAC (Heating, Ventilation, Air Conditioning) provision of voice control for curtains, lights, temperature, locks, TV and entertainment systems and support for AI based translation, so visitors can understand all television channels irrespective of the languages that they use. They also should be able to order room service in the local language via AI translation too. 

Hotels could also consider providing some of the range of digital devices now available to assist in sleep augmentation. (see previous posts). As it has been shown that people do not sleep well in strange environments. Typically on the first night anywhere new, one hemisphere of the brain does not turn off and remains on alert through this first night, leading to less restful sleep.

Other features such as instrumenting the plumbing should make it easy to centrally monitor rooms for problems with leaks etc. and IoT enablement coupled with presence detection should allow for efficiencies to be made in room heating and cooling. Other automation devices such as robot hoovers are a natural application within a building which has a high requirement for daily cleaning and a fixed layout. Operationally, they should contribute to greater room performance and availability. 

Given machine learning's capabilities, it should also be possible to match guest lists with people's cultural backgrounds, previous ordering habits and stated preferences (when booking or entering their details into loyalty scheme systems) to ensure that menus are tailored on a daily basis to what is not only seasonal, but also meets the needs of guests, increasing the likelihood that they will spend on meals within the hotel, rather than going out to dine. Similar principles apply to the stocking of bars and menus for room service.

Delivery of room service meals, drinks and other supplies such as spare tooth brushes can also be effected using RPVs (remote piloted vehicles) for a significant proportion of such transactions. Typically this could shave 15-30 minutes off the wait for a room service request to be fulfilled, doing away with those annoying waits when staff are over stretched.

Checkout, just like check in, could be greatly streamlined. Almost everyone pre-authorises a payment card these days. So the only real issue is dealing with any queries about a billing or  with any complaints as typically 4 out of 5 checkouts are just confirmation of what everyone already knows and receipts can be provided electronically. So if a busy guest just wants to check out, all they should do is enter a swipe out code via an app, and house keeping can immediately add the vacated room to their list.

Finally, a guest's activity during his or her stay, provides a trail of data rich events which can be mined for insight into overall guest behaviour as well as individual tastes and needs, leading to optimisation of future marketing efforts and incentives for repeat business aimed at all customers, specific cohorts or just the individual. This includes increased flexibility in pricing to match capacity, demand and financial yield. Although there are also context based insights for planning refurbishments and room maintenance to fit better into periods where demand is either less intense or less profitable.

So the new hotel is coming, more automated, less frustrating and increasingly tailored to the traveller's needs.

Human 2.0 - The State of the Art

What's Needed for HCI

Human Computer Interface based technology is already here in many simple forms. However, in a previous article, I mentioned that lots is needed before a mature and safe implementations can be accepted with minimal risks of Sci-Fi type Terminators or the ability to hack implanted technology (see Stealing Light by Gary Gibson for a reference).

In a previous article I mentioned some pre-requisites which are summarised in the diagram below. 

Basically, we need to crack not just the ability to interact with technology, but some quite meaty problems around dealing with information overload, shifting contexts of use, human psychology, individual preferences and behaviour, security, future proofing and dealing with the inevitable SNAFUs that technology incurs.

One of the key issues will be how much is the technology wired into us and how much will be accessed in a wearable manner.

In the meant time there are a whole host of areas where universities, the defence establishment and consumer led technology companies are developing one-off single application devices and demonstrators.

Some of these are mentioned below.

Health Monitoring

There's lots of activity around the sports and wellness area of wearables. Well established capabilities in clothing, watches, rings, smart insoles etc. include capabilities for tracking and analysing: footsteps (pedometers), heart rate/pulse, temperature, tread patterns/gait. There are devices for looking at blood flow, but these can be easily fooled.

The latest announcements extending the commercially available repetoire to include:

• Omron's forthcoming Heartguide which promises to deliver accurate blood pressure monitoring (countering reports that many smart watches are innacurate);

• Fitbit's hint that it will be delivering blood sugar monitoring technology.

There's also a lot around relaxation and sleep improvement, which I have covered in a previous article.

Treatment
Increasingly, medecine is beginning to adopt devices which are not just wearable but implantable. These devices not only monitor conditions but can deliver therapy, usually via drugs. However the most dramatic is probably the system used for epilepsy, Resposive Neuro Stimulation or RNS. This is placed within the skull and mnitors EEG signals, an electrode is placed on or in the brain at the area where seizures normally occur. This recognises patterns leading to an attack and delivers electrical neuro stimulation signals to dampen down any attack.

Mental Capabilities

There are a few interesting niche applications such as Brainco's  application for monitoring student's focus during lessons and study (to provide feedback for self improvement) and Foc.us's brain stimulation device for improving computer gamers' reaction times.

Thought Reading

It's well known that Elon Musk and Facebook rivals are looking at technologies for reading thoughts. Though at present the most accessible device is AlterEgo - a wearable device which can read words that users are thinking about produce by MIT as a research demonstrator.

An interesting article on brain controlled gadgets can also be read at Hongkiat's site.

Cyborg Extensions

Additionally, whilst the military experiment with power assisted exoskeletons for combat soldiers, there are any number of devices now being used as prostheses to replace limbs or to by-pass problems such as severed spinal cords to convey nerve impulses along broken nerve pathways.

Lockheed Human Universal Load Carrier (HULC) exoskeleton

Call To Arms

The logical conclusion is that point applications will be replaced by suites of applications, so a common architecture and interoperability is needed. Additionally, there are potential risks with some of the technologies proposed, especially if they are used by operators of high capital plant, equipment or transport. Safeguards are also needed to avoid unintended self harm from adoption. 

So before we blunder too far down this path, we need to do something to address the ethical framework for deployment and an industry certification scheme for security and personal risk mitigation.

Applying Change Management to Change Management in The Digital Era

Change management programmes have a bad image. Ever since Kotter pointed out their massive failure rate (70% to 80% depending upon whichever source you consult) and identified his 8 principles for change management, little appears to have changed.

Leaders still don't understand their role in change management; over long top down programmes get foisted on the business; if the programme gets There, There has already changed when it arrives and the world has moved on. In the process organisations often she up to 20% of their talent and the whole enterprise can get distracted from its day job, hitting organisational performance badly. So the only remedy becomes, launching another change programme.

Change is fundamental to Digital Transformations since not only is a business trying to adopt new technologies to support innovation, it also has to change its business model, organisation and skills to do this. So how do businesses cope? A great quote is by George Westerman of MIT's Sloan Business School “When digital transformation is done right, it’s like a caterpillar turning into a butterfly, but when done wrong, all you have is a really fast caterpillar.”

So what's new? Gartner reckons that 66% of Success Factors are related to talent. Yet the Scrum Alliances recent survey of global CxOs indicates that HR is one of the least Agile functions in most businesses. So its time for leaders to be leaders and work with both each other and their teams. As there's a fundamental signal coming from so many sources that Culture is the over riding discriminator in success. Getting the balance right between direction setting and team driven empowerment and innovation is fundamental.

Secondly, whilst having a clear vision of what the destination looks like, the trend is to break the journey down and only attempt the first few steps before re-calibrating. As the famous Chinese proverb quoted in Chairman Mao's little red book says, "Even the Journey of a Thousand Miles starts with a few small steps". 

Looking for small wins and business along the path of massive change, allows for experimentation, learning and course correction. So that a business navigates to a desirable destination and does not just follow a mirage.

Finally there is a heavier trend towards Data and Insight. Many innovation efforts rely heavily on data to validate (or otherwise) hypotheses and experiments, as well as to provide new insight. This has to be set against deep industry knowledge and intuition. Change involves both art and science to deliver effectively.

Business Leaders need to understand that Innovation and transformation means doing things which have not been done before (not just the same old things faster and better). So they need to be enquiring about the art of the possible, challenging about what really is the nature of value and how actions align with them, and liberating in the way that they encourage their teams to be part of the solution (rather than the unwilling victims of good intentions).

Culture Shows Up Again as the Thing Driving Agility

Forbes Insights and the Scrum Alliance have got together to publish a recent report on Organisational Agility, drawn from interviews with over 1,000 C-suite executives from around the globe.

A key theme which runs through the whole report is how important Culture is to Organisational Agility. (Something which I emphasised in "The Way of DAU"). Additionally, there are some compelling findings about the benefits of organisational agility. Over 50% of respondents identified benefits in the areas of:

• Time to Market
• Speed of Innovation
• Employee Morale
• Ability to Attract Talent
• Competitiveness
• Financial Results
• Ability to Manage Across Geographies

To re-inforce these findings, the report focuses on the performance of leading Agile Organisations and Laggard Organisations. Whilst they represent similar proportions of the overall survey population (16% and 19% respectively), twice as many Leader Organisations enjoy annual growth of over 20% as Laggards do.

In all probability, the CxO community that the authors consulted, probably included a pool of organisation most interested in Agility, as an earlier report by McKinsey suggested that only 4% of organisations have completed an organisation wide Agile transformation.

The report looked at a number of things, including whether organisational agility was End-to-End or siloed in functions. Based on the opinions of the respondents, it appears that Operations and Technical Functions tend to be the most Agile (79% and 75% respectively), followed by the usual suspects in Sales and Marketing. Interestingly enough, Finance achieved a credible 64% vote of confidence, but HR was amongst the laggards with only 56% of respondents considering it an agile function. Considering that HR is often thought of as the "Guardian of Culture" this is a worrying gulf and should be a wake up call to HR to re-vitalise its mission.

One area that I would have liked more analysis on, was whether Leading Agile organisations already had positive innovative and collaborative cultures before they embraced Agile or had to focus on it as part of Agile Adoption.

Anyway, the take away is that all CxOs, irrespective of function, need to work on fostering the right culture.

Digital Sleep Tech Proliferates

We spend almost a third of our lives sleeping, yet we are still amazingly ignorant about sleep itself. We know though, that modern living has disrupted our whole approach to natural sleep and that electric lighting is so prevalent, that not only do we not align ourselves with the natural patterns of going to sleep soon after darkness falls and rising with first light, but that we live in a "light polluted" environment which increasingly makes it difficult to go to sleep.

As someone who used to travel a lot for business, I hated trying to sleep in hotels. Not only was I in an unfamiliar bed, but hotels are often quite noisy at might and modern hotel rooms are full of electronic gadgets with LED lights which glow in the dark. I used to lay towels over the crack at the bottom of the door and turn everything I could off at the wall or place room service menus in front of the offending lights. I also tried a sleep mask, to limited effect. so it was interesting to see recent research which suggests that one brain hemisphere usually stays active all night when someone sleeps in an unfamiliar place. This effect has been described as akin to having a neurological night watch.

More interestingly, scientists have also re-discovered the fact that people used to sleep naturally in segmented sleep patterns, usually of two stretches of about four hours each. Roger Ekirch published a book in 2001 documenting over 500 literary references to first and second phases of sleep at night. A pattern which appears to have begun to be disrupted in the late 18th century as growing affluence and changing technology gradually eliminated our natural sleep patterns.

People tend to worry about their appearance if they don't sleep well, as this causes unsightly dark rings and bags under the eyes. However there are more serious physiological effects. Recently, scientists have begun to link poor sleep to obesity, heart disease and diabetes, as well as a host of other side effects such as grumpiness and having a low sex drive. Also, numerous studies have shown that poor sleep can affect driving ability as much as alcohol consumption. Working night shift is also considered a factor that can cause factor according to the World Health Organisation and studies have shown that nurses who work extended periods of night shifts, tend to die prematurely.

So it is interesting to see what is happening in the Wearable Technology space to help people improve their sleep, as several interesting devices have come to market in the last year. These devices contrast with others such as muse from interaXon which is focused on relaxation and meditation and aim to improve sleep quality.

Insomni Light - This is perhaps the simplest device on the market. Basically, sleep scientists tend to talk about 4 different states characterised by brainwave activity. The Insomni-Light sleep mask uses LED lights to relax the user, which it claims will help take your brainwaves into the Delta state associated with deep restorative sleep. At present this is just about to go on sale.

Cereve Sleep System from ebb - This basically uses a head band  on the forehead to cool your head (and brain). A bedside unit supplies cool liquid to the head band and maintains it at the required temperature. Ebbs site claims that 80% of users find that this improves the quality of their sleep. The site also claims that this is FDA cleared for safety and effectiveness.

Dream - from Rythm -  this is a device that I personally use and have written about before. It is a headband which helps you get off to sleep by using several different strategies: playing soothing sounds, helping you time your breathing to encourage sleep, or meditation to break agitated thought patterns. It also monitors your sleep and, whilst you are in deep sleep, it plays you "pink noise" to improve the quality of deep sleep. It will also bring you gradually awake by playing gentle noise during light sleep around the time your alarm is about to go off. It is claimed to improve deep sleep quality by up to 30%. My experience is that it improves over time and that I average just over a 20% improvement per night, although his varies considerably from night to night; on my best night ever, I got an 80% improvement.

The information that it provides is useful feedback and I have learnt a lot about my sleep from it, as yes, I am sad enough to plot it out on graphs using a spreadsheet. It seems that typically I spend 20 to 40 minutes per night in Deep Sleep. Although on one memorable night I achieved 119 minutes of Deep Sleep. I also tend to spend about 80 to 120 minutes per night in REM Sleep (the state usually associated with dreaming). Over the period that I have used it (about 8 weeks) the amount of Deep Sleep that I get every night has increased by around 5 minutes which is a lot when compared with a typical 20 to 40 minute period. My REM sleep has also increased by about 15 minutes, which again is a significant percentage increase, .

The period that I actually spend asleep has not changed significantly, at not quite 15 minutes per night, compared with a typical night's sleep of 6 hours twenty minutes (or 380 minutes) or under 5%. So the material improvements have been in quality rather than quantity. As REM and Deep Sleep are both considered beneficial. This is witnessed by the fact that I feel less tired and have lost the deep circles under my eyes which were there previously.

NuCalm - ReNu headset - This is part of an overall system utilising suplements, electrodes, the headset and a sleep mask. The electrodes provide microcurrent stimulation in the form of beta and delta waves associated with REM and Deep Sleep, and the headset provides sounds (which ReNu calls neuroacoustics) to relax the mind, deal with stress and assist with sleep.

Although this is a very complete system, it is not designed like the others specifically for sleep, so may be a bit clunky for people trying to just improve their sleep. 

Thynk Relax Pro - This is a device which you attach tot he back of your neck. It uses electrical neck stimulation to help you relax and improve sleep.

Common to all of these devices, is the need to use them over a period of time to achieve noticable improvements. As these are all promising 1st generation products, I would expect that we shall see evolution and enhancement. There may be further crossover to integrate all approches: light, sound, cooling and electrical stimulation. There may be further features to work on sound cancellation, as none of the products considers the impact of ambient noise on sleep. Additionally, I would expect improvements in form factors to improve sleep comfort and avoid headsets falling off during the night. Furthermore, feedback and use of machine learning is bound to improve overall effectiveness and the tailoring of device performance to individual users. However, I think it is safe to say that a New Dawn on sleep improvement and self help has arrived.

N.B. all pictures were copied from the manufacturers publicly released pictures on various websites and the copy right does not belong to me. So please respect these rights if you intend copying and re-using for any commercial purpose.

Artificial Intelligence and Our 5 Senses

Artificial Intelligence (AI) is very much the thing of the moment. A lot of new enterprise models appear to be built on a combination of AI, IoT and Big Data to collect and process massive amounts of data and to apply human like skills of recognition and decision making with a level of consistency, speed and volume that was previously unattainable with conventional processes or systems. This leads to greater insight, improved performance, better use of scarce skills and consequently other benefits such as improved customer experience, better security and higher cost efficiency. It also means that some tasks which would never have been practicable before are readily delivered via automation.

However when we look at what a human can do, AI capabilities are still lacking. The human capability to use our 5 senses, think abstractly, innovate and test hypotheses, to develop new learning are still a challenge to AI.

Just focusing on the 5 senses: Sight, Hearing, Touch, Smell and Temperature, AI's progress is quite patchy.

In the past 30 years or so, AI's ability to deal with vision and speech has progressed from a miserable score of  about 1 to 2 out of 5, to a 3 to 3 and a half out of 5. Handwriting recognition works well with typed characters, but still has a significant error rate with hand writing. Face recognition systems work quite well with caucasian faces but apparently struggle to deal with black african faces. It is not clear to me  whether the latter is to do with poor training (i.e. not been given enough sample data for adequate deep learning), fundamental flaws in the assumptions made when designing the systems to recognise features or some problems with technical measurement of contrasts and camera sensitivity across the visual spectrum. Whatever the problems, error rates are still quite high.

Temperature is quite easy with thermo-couples and can be engineered to deal with temperatures that people could not with stand. So high marks of 5 out of 5 are to be expected.

Touch has been a major area of research ever since robotics became a hot topic in the late seventies. Most of the work so far has focused on sensing around grip, so that a robot could pick up an egg or some other delicate object without crushing it. But I have not seen anywhere the type of sensing that could differentiate between the touch of skin, rubber, silk, cotton and wool. So this definitely languishing in 2 out of 5 territory.

Smell has barely been touched. However some work is suggesting that techniques for smell processing, which mimic natural biological processes could be invaluable in extending AI capabilities to deal with situations where learning data is limited, ambiguous or masked with other "noise". Smell has potentially many applications in medecine, agriculture and food processing. The techniques however, may be useful for Autonomous Unmanned Vehicles which often have to deal with unforeseen situations or noisy environments.

So there still a long way to go for AI to reach science fiction like capabilities. Conquering the 5 senses represents the first step. The question is, how long will this take and will all humans be machine augmented, by the time we get there?

Would You Follow This Advice?

According to a recent Harvey Nash / KPMG survey, businesses are increasingly looking to CIOs to improve customer experience and to deliver capabilities which grow new revenue from both new and existing customers.

At the same time Gartner is touting a model of 4 strategies to do this, summarised in the diagram below.

However, I have a problem with this as a strategic tool. To my mind, it is very bottom up and not very illuminating beyond stating the fact that you can exploit various tools. It does not actually connect with business value or scenarios that businesses may find themselves in. It would appear to drive the kind of thinking which says "I've got 4 hammers, what size nail do I need to solve this problem", rather than "what is the real problem? do we actually need to do anything? what are our options? how would we best address this quickly, to appropriate quality (& value) and can we do it economically?" Digital Strategy should be about "how do we deliver new and unique value?" not about "here's some solutions, let's find a problem to fix."

Should Your Next Startup be in Sao Paulo

A decade ago, everyone was waxing lyrically in the received wisdom of the BRIC phenomena. The 4 fast growing economies of Brazil, Russia, India and China. After a while I started to notice that Brazil was sending representatives to IT conferences and other fora to promote Brazil's tech industry.

So why is this important? Well Sao Paolo is known as the manufacturing centre of South America and Brazil with a population of over 200 million is considered the 8th largest economy in the world. Against this ranking, Brazil's IT industry representatives present Brazil as having the 7th Largest IT industry in the world. So it should be important.

This leads me to the question of why don't we hear more about Brazilian Startups and why isn't there a stampeded of people from the UK and Europe trying to invest in or partner with Brazilian startups? So I decided to  enquire further.

It appears that investment in Brazilian startups is healthy. A Financial Times article, places Sao Paolo 11th in the world of any city attracting startup funding rounds greater than $100M. This places it behind London, but ahead of Tokyo, Paris, Seoul, Austin, Seatle, Tel Aviv and Mumbai inter alia. So Brazil's reputation for high costs and bureaucracy is not putting anyone off (a lesson for Brexit remoaners perhaps).

So why don't we hear more of this in the UK. One answer could be that Brazilians are notoriously conservative and don't like to do business with people with whom they do not have a long relationship. Additionally, they like quid pro quo partnerships, so want you to bring something more to the table than just cash. The other may be that traditionally they are quite insular in outlook and compare themselves with the United States only. So startups like Pipefy and Psafe have looked to the US rather than Europe. 

I think it's time that UK entrepreneurs started to explore the opportunities available in Brazil, as there is a huge talent pool there and loads of innovation. Personally, I think it's time to do a duolingo course on portuguese.

Are Businesses Still Missing the Point About Digital Transformation?

The other night I was talking to the Head of Product Management for a company who run several Dating Site brands (facing into differnet market sectors: young, old, gay etc. and across over 50 countries). He was really keen on the term "Digital As Usual" (DAU), because it encapsulates the culture and thinking needed to sustain a Digital Business Model.

So I was quite disappointed to see Raconteur's recent article on Digital Transformation, which shows just how badly many companies are still addressing their move to a Digital Business model. The usual collection of issues showed up: It's an IT problem, its a siloed CDO problem etc. Though, to some extent I think that the authors and experts quoted in the article got it wrong too as they keep talking about Digital Transformation, implying that you get there in a relatively short period of time. The whole point is that you never get there. It is a continuous journey and requires the whole business to act as a team who enjoy voyaging. So instead of transformation programmes, they should think Star Ship Enterprise and understand that what they are really pursuing is organisational excellence and customer delight. Getting that right will move the dial on meaningful organisational measures of performance and deliver revenues and profits (or whatever relevant Value that applies to their organisation) as a byproduct of operating a successful Digital Business Model.

What was interesting in the article was the criticism of organisations who think about digital as just being IT. Whilst in Asia Pacific, a recent survey looked at Digital and IT Transformation. Companies in this region belivve that they are leading the world in digital transformation. Its finding was that where businesses had addressed IT Transformation, they were over 39 times more likely to make better faster decisions than competitors and 13 times more likely to complete application deployments ahead of time, whilst running their critical applications at less than half the cost of competitors (who had not transformed). This is despite the fact that IT leaders are less likely to be involved in critical business decisions that in other parts of the world.

So, IT and lean capabilities are essential enablers, but the senior management team needs to work as a team and not a series of siloed prima donnas. However it is difficult to find anyone who works maturely across all aspects of digitalisation. The Head of Product Management that I talked to (above) freely admitted that his organisation, although growing successfully, does not put enough attention into data quality and avoiding technical debt. And the Strategic Busines  KPIs that they work to are not perhaps the best in optimising customer experience. However, they were very storng on identifying tangible market opportunities, product thinking and lean delivery, whilst enjoying a positive collaborative and innovative culture. They recognised that innovation does sometimes mean learning from failure, although they don't have a strict measure on how much failure is acceptable. But they were doing enought to prosper and continue to learn and grow on their journey. And that is the point.

Aligning Digital Exploitation with Operational Capability

All Enterprises Are Not the Same

One of the tenets of Digital As Usual (DAU) is that most businesses are not pure play digital organisations. In almost all cases there are operations and activities which are essential to either fulfilling service or delivering a product which need to be managed as well. The Digital Adoption Framework assumes an Industry Categorisation Model as illustrated below.

The Industry Categorisation Model identifies 5 Categories along a continuum of Industry Product Nature. At one end of the continuum are “pure play” digital organisations, whose products are Information and Content based. These consist of Market Platforms like eBay and Compare the Markets.com who provide a platform, through which other organisations and people sell their goods and services, as well as Publishers and Providers of Content who provide videos, e-books, podcasts, news, music etc. At the other end are Extractor and Grower type businesses, such as coal mines and cocoa growers who provide natural unprocessed products. Off course not all businesses fall neatly into just one category. A major energy company such as Shell or Exon may straddle several categories along an Upstream (exploration, drilling and extraction) to Downstream (transport, refining and distribution) activities.

So why is this important when thinking about digital businesses? Well each different type of business operates in different ways, has a different level of dependency on capital assets and has different opportunities for exploiting digital technology to augment its business model. Additionally, the whole concept of Lean Delivery via Design Thinking, Agile Delivery and DevOps may have different opportunities and constraints as well as nature of delivery in each category.

Some Examples of Exploitation

The diagram below looks at the potential for exploiting Artificial Intelligence (AI) technologies according to Industry Category.

The “X”s in the table represent significant opportunity for exploitation against a generic type of Use Case. So for example AI technologies (machine learning, visual recognition, natural language etc.) can be used to provide insight and learning in every type of organisation, but there is very little opportunity for them to add to “customer experience” in say mining or farming. Again there is huge potential to build AI capabilities into consumer products, e.g. Alexa in Amazon’s Echo, but there is little opportunity to enhance a product such as iron ore or tree trunks produced from a Natural Product Extractor or a Grower. 

Alternatively for IoT, see diagram below, the opportunities are pretty limited for an Information publisher, but there are many areas where a farmer could use it to track livestock and monitor soil conditions and crop conditions, as well as control assets such as vehicles and trailer equipment.

This moves us onto exploiting iterative approaches within an organisation. The other night I was talking to someone from a major pharmaceutical company. Drugs take years of research to identify promising candidates for a problem and to test for efficacy and safety, as well as meet regulatory demands. There is little opportunity to exploit Iteration in this type of product development. But for the company overall, there are opportunities around internal processes and with Agile Marketing.

Agile Marketing is a growing area of adoption within industry and works well for consumer driven businesses. At its core is the use of small integrated product teams which focus on market research, product promotion, delivery of marketing and promotional materials, advertising and the information analysis systems used to support marketing data analysis. These teams tend to work in multiple sprints testing out marketing promotion hypotheses and rapidly identifying which approaches produce optimal results, to improve overall revenues. 

Iterative development also its quite different for delivering an oil tanker or a film, to the development used to support a consumer service. In the case of the former, iterative design, development and continuous testing techniques are used to deliver a single integrated complex product over a period spanning many months if not years. In the latter they are used not just to deliver the product, but to continuously keep it fresh, up to date and moving ahead of competition that is playing catch up.

So it's important not to adopt a one sized fits all approach, but to really get down to what can work for your organisation. This is part of what I talk about in my book.