Be Digital or Be Digitalised

In a conversation with a colleague the phrase “be digital or be digitalised” emerged and it started me thinking. The discussion of the 3 laws of digitisation can be summarised in this simple phrase. We all need to look for the activities that can be digitalised and/or automated. This leads to the question, how? This is where we need to become a little savvier than just being the annoying person pointing out that all these activities will be digitalised. A little more subtlety here. Whilst many things can be digitalised does not mean the should or will. There is a cost associated with the effort for digitalisation and unless there is an adequate return, it might be best to leave this in a non-digital form.

As a simple example, it light switch can be replaced by a digital switch. However, most homes have kept this as a manual switch. You might switch the light on a few times a day and the switch is in a convenient location so the cost and disruption would be difficult to justify. However, in an office where lights are left switched on, an automated switch with motion sensor could reduce the energy usage. There is a clear rationale and many offices have made this change. There will also be a group of people who say that they forget to switch the light off at home in the morning and they have returned on the evening to find the light has been on all day. For them, you could argue a digital switch, with motion sensors and the ability to check the status of the lights in the house may be justifiable. Also, you might prefer a range of lighting options – the colour, the brightness, which parts of the room are lit etc. Whilst you could imagine a bank of switches to control this range of settings, it would be much simpler to create a digital control and so digitalisation would be appropriate.

The march of digitalisation is moving at an ever-accelerating pace and we need to stay ahead of this if we are to continue to gainfully employed. Activities in our work and personal life will be changed through digitalisation. We have a choice of deciding to wait for this to happen and then respond or we can be the ones driving the digitalisation. There is no right or wrong here, it is a choice we all have to make. My concern is that lack of awareness of the potential for digitalisation results in a sudden shift and creates unexpected disruption. This is where we need the most help. Being aware of the current possibilities, and challenging yourself to spot the opportunities for digitalisation is a vital skill for survival in the digital economy. Where do you start? Simply start by asking your colleagues, on a regular basis could we accelerate or simplify what we are doing through digitalisation?




Are you catering for the spectrum of digital skills?

I just read the UK Consumer Digital Index 2018 report with great interest today. Some of the statistics where sobering are best and alarming at worst. An estimated 4.3m people with no digital skills and 11.3m with basic digital skills. Which probably means that 11.3m people have little chance of reading this blog post and 4.3m would only be able to read this blog if someone printed it for them or read it to them. On the positive side, the report does show progress since last year.

Many questions came to mind as I read the report, starting with do we take this reality into consideration when designing digital services. Do we focus effort on growing the basic digital skills in everyone? Or do we focus on providing choice to these significant number of people who are cited in the report as having no interest in developing digital skills.

As the disruptive force of automation and digital disruption continues to replace aspects of work and in some cases totally report jobs, what is the implication for those with no digital skills? Will there be sufficient non-digital jobs to keep them gainfully employed?

Whilst all the data needed to answer these questions is not readily available in a form to be able to provide evidence based arguments, is it best to just focus on growing the digital skills in everyone. Is there anywhere in the world where everyone has basic digital skills? If not who will be the first?

Lots to consider here, I would be very interested to hear everyone’s views and any links to data would be very valuable.

How can creating a hassle map help you build your Digital Economy Platform Strategy?

Over the last six months, there has been a surge in interest in establishing digital platforms – primarily multi-sided and create an ecosystem to amplify/accelerate value capture. In most of these discussions, people can articulate the challenge they face from competition that will mean they need to cannibalise their existing business to survive the onslaught from start-ups. In a previous blog, I talk about creating certainty as one way of finding the purpose of the platform. There are a number of other techniques that are valuable here. You can use the 5 patterns from the HBR paper I co-authored to help identify the strategies.

Another very useful technique is hassle mapping. I first came across in Adrian Slywotzky’s Book – Demand. This forces you to think from the perspective of the final beneficiary of the platform. Creating persona using a technique such as IBM’s Design Thinking can help here. The hassle map will help in identifying the experiences or service that will be of sufficient value to be paid for.

There is a lot of information on hassle mapping on the web:

I am keen to learn from others in this area. How are you developing your strategies in this area?

Excellent example of data to outcome

Remember the 3 equations that summarise the logic for how data can create an outcome. I just came across an analysis done by Venkatesh Rao where he explores the 1854 London cholera outbreak. What is most interesting about this is how the raw data when put into the context in the final map shows how Dr Snow’s hypothesis is validated by plotting the data onto the map. The map in this case is providing the context and provides the insight that the Broad Street pump is most likely contaminated. His action to remove the pump validates the actions and cholera cases subside.

Excellent analysis and provides a valuable illustration of how data can create remarkable outcomes.

Is the removal of uncertainty at the heart of the digital economy?

Creating magical client experiences that become viral and scale exponentially summarises the approach of digital economy leaders. But what is a magical client experience? As I considered this question I started looking at examples of “magical experiences”.

The first example that came to mind was seeing the expected arrival of the next bus on a digital display at the bus stop. When I first saw this in London I remember discussing this with everyone I met that day. This is now readily available and anyone can build an app to provide this information using the TFL as an Open Data API. However, at the time this was a magical exerience.

The second example is using Flight Stats to check on the status of flight arrivals. I was travelling to the airport to meet visiting relatives and we were stuck in a traffic jam. Previously the only means of checking the flight status was to phone the airport, some provided an information service. The first time I was able to open the FlightStats website and see the arrival information, I knew that the flight was delayed and I did not need to worry about getting to the airport in time.

Considering Uber – what was magical about their experience? If you remember having to phone for a taxi and the controller saying the taxi will arrive in 10 mins. After 15 mins you would get frustrated and phone the taxi company again to ask when the taxi was due to arrive. The polite operator would re-assure you that the taxi was on the way and will be with you soon. You were relieved that you had requested the taxi with plenty of time as you had little confidence in predicting how long it would take for he taxi to arrive. With the Uber experience, you are able to see the location of the taxi, get details of the taxi and the driver. This removes the uncertainty that existed before and creates the magical experience.

As we consider ways to create value in the digital economy, the uncertainty that exists in a process or for an individual provides an ideal starting point. Questions such as, when will this device need servicing? What is the condition of the critical elements of the machine? Will the house be warm when I return? When did I last meet this person? These kinds of questions can help identify the outcomes that can be achieved and also estimate the value to be captured. It also helps identify the data required and the supporting systems/technology.

So is the removal of uncertainty at the heart of the digital economy? What is your view?

Is the economic value data derived from connections?

Life sometimes seems impossible to rationalizas discrete objects or eventsBut, if you start to consider the connectivity around youtapestry of links emerges based on, what appears to be, a finite set of rules. In this way hands are connected to arms and friendships are made through the casual sharing of ideas and kinship. Considering data like this can therefore help uncover previously hidden patterns. That is, if some established scientific approaches are appreciated alongside. For example, the four laws of thermodynamics point the way to some very useful techniques for understanding the inherent value in data (or more precisely information). 
At surface inspection such laws might seem detached from the idea of information, helping instead to describe physical properties like temperature, energy and entropy. But history tells us how they proved essential in the early development of Information Theory. This then provided a valuable way-point on the road towards more contemporary ideas on how information chooses to connect and structure in the wild. One such idea is that of scale-free networks – networks that maintain their essential characteristics regardless of how large they are. These can be found in the the distribution of popularity of websites across the World Wide Web, or the way that consensus spreads through a social network. Similar patterns emerge from the analysis of economics data, or most other fields of human endeavor.
Uncovering patterns like these is critical to the progression of digitalisation and extracting value from digital data at scaleOne can think of uses such as predicting market crashes and developing laws for prediction surely gives us an indication of the advances needed to uncover the underlying laws of human behaviour and the complex systems that intertwine our lives. Interdisciplinary collaboration is needed to advance our understanding of complex data sources, however. As explained by the authors of Superforecasting: The Art and Science of Prediction increased accuracy comes from combining insights from multiple sources and fine tuning the probabilities. 
To find your space in the digital economy a combination of skills and techniqueswe have depended on for many years, needs to be applied in creative ways to find those hidden patterns, develop the laws and thereby  help reduce inefficiencies and create value from the data.
Written in collaboration with

What is digital infrastructure?

Many governments and cities are discussing the importance of investment in digital infrastructure to maintain competitiveness. Sounds a very sensible and effective strategy, but this rises a number of questions.

What is infrastructure?

This might be obvious to many people, however, if you ask a group of people, you would get a range of answers. This wikipedia article elaborates the ideas of infrastructure and introduces telecommunications as a contemporary infrastructure.

What is a digital infrastructure?

Often government leaders assume that digital infrastructure refers to the internet or high speed broadband. The analogy is that of roads that allow the movement of goods between locations.  The digital infrastructure needs to allow the rapid movement of digital data between locations. So it is natural to think that super fast broadband is the answer. This analogy is a good starting point, but misses some differences between road networks and data networks.

Why does data need to move between locations?

Data needs to move to the place where a person can view or make use of that data. For example viewing a webpage or launching a connected app on a smartphone. This is at the edge of the network, however, there are much more complex interactions that are not seem by the consumers of data. Drawing connections between pools of data, analysing data requires the data to move to algorithms or algorithms need to move to the data. A search engine such as Google is constantly accessing websites to capture changes or identify new websites. Data is being backed to be re-accessed in the event of failures.

The cities data infrastructure needs to cater for a wide range of interaction patterns as well as data storage and  analysis. Using the road analogy, the design needs to consider car parking, placement of warehouses for trucks, and pedestrian zones. In the same way the city data infrastructure needs to consider data centres, open data platforms, mobile phone network access etc.

What is the value of the data and what infrastructure can the city afford?

Firstly, we need to remember that it is the use of the data that helps  create value. The three equations I described in a previous blog post help in identifying the role of digital infrastructure.

  1. Capturing data and making this available for analysis. Open data is particularly important in creating ecosystems of innovators.
  2. Access from analysis. Allowing all types of appropriate access to algorithms that will turn the raw data into information that in its own right can allow a range of decisions and uses.
  3. Creation of models or context system that identify new insights. Identifying anomalies, deviations or correlations that will inspire new actions. Ultimately the actions are the means of creating value from the data.

So the digital infrastructure for a city needs to cater for these uses and be priced at an affordable level for the organisations or individuals.

Cities should start by understanding what data is needed to satisfy the citizens, the business and institutions. Then the range of data facilities that will be satisfy these requirements. Then determine which of these elements are best provided via a city wide digital infrastructure.