Could you be a Digital Superhero? Julie Dodd (Camp Digital 2016)

Here’s a summary of Julie Dodd’s talk at this year’s Camp Digital conference.

Julie argues that digital superheroes…:

  1. Make products that really help people

    e.g. the Ugly Mugs app, built for sex workers to make sex work safer, or Tony Canning’s use of 3D printing to reduce the cost of prosthetic limbs from £20,000 to £40 – and reducing production time from months to hours – and making the technology available open source so that others can use it.

  2. Use any tool or platform that they can get their hands on

    BBC used Whatsapp at the height of Ebola in Sierra Leone in 2014 to provide information. Largely simple infographics. Reached 20,000 people in the first 3 months who were otherwise very hard to reach. The BBC used existing technology as it was cheaper, quicker and more effective.

    Crowdfunding sites – e.g. Kickstarter and IndieGogo – reduce the need for people to go through a middleman. Charities need to think what this means for them.
    Girl Scouts in America used IndieGogo to raise funds after rejecting a $100,000 transphobic donation. The troop of Girl Scouts that turned down the donation started a crowdfunding campaign that raised 4 times as much money – and sent out a powerful message about inclusion. They also changed the policy of how the national organisation takes donations.

  3. Aren’t frightened to try new ways to do things

    For example bringing in service design thinking or agile methogologies.

    St Mary’s Hospital in Paddington has created the ‘Helix centre’ innovation lab. It’s focused on lean, iterative solutions and combines online and offline. Projects include increasing rates of bowel cancer screening, offering guidance for clinicians on how to communicate about end of life care, asthma management tools for kids, dealing with storage of IV fluids.

    The Town of Jun use twitter for civic discourse and interactions – e.g. booking an appointment with the doctor or making a complaint. Everyone was trained. Saw a rise in public workers being thanked.

  4. Can be found anywhere – not just in tech.

    Google studied a favela in Rio, and didn’t expect to find much technology. Rather, they found a flourishing ecosystem, with radio stations, cyber cafes. With the proliferation of smartphones, people often ‘leapfrog’ the desktop ‘stage’ of development.

  5. Can have significant impact on organisations.

    The British Library now conceives of itself as a data institution, rather than a custodian of physical objects.
    The #tweetmythesis movement encourages academics to share their thesis in a tweet.

  6. Can have an impact in major commercial brands too.

    Barclays set up Digital Eagles programme, driven by the profit motive of reducing cost by moving more people to online banking. (And thereby reducing interaction costs, e.g. staff and branch costs). So it has trained 20,000 staff to train people across the community.

  7. Should work for organisations interested in changing.

    When researching “The New Reality” Julie found some organisations just weren’t interested in digital transformation. She thinks many won’t survive a decade, and wants to spend her energy not fighting those ones to change, but working for the ones that do want to change.

A few miscellaneous recommendations:

  • Recommended meetups: Citizen Beta and Tech for Good
  • “Apps without marketing are pointless”
  • If you do pro bono work with a charity, make clear the equivalent financial value. Otherwise they won’t value it because it’s free.
  • “Asking people to experiment is easier than asking them to commit”

Design for Real Life

Design for Real Life argues that we need to take accessibility more seriously. This goes beyond just conforming to a set of content presentation guidelines (e.g. the W3C standards), and goes to your overall design process. You can buy the book from A Book Apart

  1. Identify and challenge assumptions

    Think about what assumptions you’ve built into what you’re designing. What will happen if someone falls outside these?

    Facebook’s Year In Review – a feature designed to help people celebrate and share their great year – wasn’t designed with the experiences of people who’d not had a great year in mind.

    Inappropriate Year In Review images included:

    • a photo of the user’s apartment on fire
    • a photo of an urn containing the user’s father’s ashes
    • a sonogram of a pregnancy that later ended in miscarriage
    • a photo of a friend’s gravestone

    Facebook’s design team had a narrow vision, and so excluded all of these users. Meyer and Wachter-Boettcher challenge us to bring “edge cases” to the centre. “Instead of treating stress situations as fringe concerns, it’s time we move them to the center of our conversations – to start with our most vulnerable, distracted, and stressed-out users, and then work our way outward.” All users will benefit from this more focused, understandable and empathetic approach.

  2. Make space for real people

    Give people “enough room within our interfaces to be themselves.” For example, gender is often presented as a binary choice between male and female, which doesn’t fit with our current understanding of gender. Facebook is an example of best practice here, allowing people to choose male, female or custom – which is a free text field with a list of common choices as prompts.

    Other examples of systems not giving people space to be themselves include systems that can’t handle names longer than a certain length (e.g. 15 characters), systems that don’t accept hyphens in names, or ones that don’t accept names that don’t pass culturally-specific test of validity. (e.g. Facebook rejecting Shane Creepingbear’s name as not real.)

    Organisations often make assumptions about what matters to users, or about who they are. The ‘Apple Health’ app didn’t include period tracking on launch, even though it boasted that it tracked ‘all of your metrics that you’re most interested in’. Its implicit focus was on men. And period tracking apps themselves often have a bias towards straight, sexually active, partnered people.

  3. Incorporate stress cases

    A DIY and home appliance retailer was looking to improve its product guides. Originally these were written in a chirpy, positive tone, for happy, confident home-improvers. But sometimes users are more stressed when carrying out these tasks. The team found that there were two general categories of use: “urgent” and “upgrade”. They updated their style guide to write for the urgent case. This improved the guides for all users, as the clarity of information increased. Guides now feature installation availability and time-frames, estimated cost ranges, greater user of subheadings to allow for easy skimming, one-sentence summaries, reassuring tone.

    You can incorporate stress or crisis cases in usability testing. And you can test how a product performs in a cognitively-demanding environment by either testing in that environment, or by tiring people out mentally before the testing – e.g. by giving them some maths tasks to carry out.

  4. Only ask necessary questions in forms

    Organisations are often pushy to obtain as much information as they can from every web form. Often this is done with a total disregard for the user’s experience. Caroline Jarrett has a protocol for evaluating each question you want to include:

    1. Who in the organisation will use the answer?
    2. What will the answer be used for?
    3. Is the answer required or optional?
    4. If the question is required, what happens if the user enters rubbish data just to get through the form

    This question protocol can help open up a discussion about the true business value of each question.

  5. Learn from users

    Work to understand how your users see the world. This goes deeper than just testing top tasks on your website, or discussing product features.

    Steve Portigal recommends three types of question:

    1. Gather context and collect detail. e.g. asking about a sequence (Describe a typical workday) or specific examples (What was the last app you used?)
    2. Probe. e.g. ask for clarification of how a system works.
    3. Draw out contrasts. Useful for uncovering frameworks and mental models. e.g comparing processes or approaches.

    Open-ended research is about opening up questions and ideas, expanding your vision and the types of question you ask. This helps you move towards a design process centred aroudn real people and their needs.

    Customer mapping can help you identify pain points, broken flows, and content gaps, through analysis of lenses, touchpoints, channels, actions, thoughts and feelings. Adaptive Path have produced a guide to customer experience/journey mapping.

  6. Making the business case for accessibility

    Karl Groves, an accessibility consultant, argues that there are only three business cases for anything. Here’s how to argue for accessibility for each of these:

    1. It will make money. You can use accessibility to stand our from your competitors. e.g. Slack gaining users through ease-of-use. You can reach new audiences if more people are able to use your product.
    2. It will save money. You can cut customer service costs. The UK government found that as of 2011 it was receiving 150 million avoidable calls a year – calls for which an online service existed. This represented a possible annual saving of around £4 billion a year. Improving accessibility saves you money by increasing user retention – which is between 5 and 25 times more cheaper than acquiring new customers.
    3. It will decrease risk. Accessibility helps you avoid negative experiences and associated backlash – e.g. Facebook’s year in review generated a lot of negative press.

Agile Planning – How to plan quickly and collaboratively

A summary of the 02/08/2016 Digital Project Managers meetup on agile planning.

Estimating jobs

Gather the whole team for this exercise. e.g. UX design, developers, testers, product managers.

Discuss each job, and collaboratively rank the jobs in order of complexity.
Think about all the work that will be required to get this job ready to go live.
For each job, some elements might take more time. E.g. UX might take a long time on one job, but the development might be quick. So you need the different perspectives involved in the discussion.

Groups similarly-complex jobs together.

Apply T shirt sizes to these groups: S, M, L, XL, XXL.

If you have anything XXL, break it down into two or more different jobs.

Assign ‘story points’ to each job, based on its size:
S: 1
M: 3
L: 5
XL: 8

(If you’re running an internal team, there’s no need to think in terms of hours.)

Estimating velocity (how much work you can get done in a given time period)

If you’re an established team, you’ll know from experience how much work you can complete in a given period.

If you’re a new team, you’ll need to collaboratively estimate how much work you think you could carry out in a given development sprint (e.g. 2 weeks).

Work through each of the jobs, and combine them into groups showing how much you think you could carry out in a sprint. Then total the number of story points of the jobs in that group.

Once you’ve done this 10 or more times, work out the average number of story points per sprint. (Round down to the nearest whole number if required.)

This is your estimated velocity – the number of story points you think you can complete in a given sprint.

Prioritising jobs to build a plan of work

Prioritise all jobs using force rank: the highest priority job goes at the top, the lowest at the bottom. Nothing has equal priority.

You can also factor in sequence dependencies (and so promote some jobs that are required to allow you to complete other, higher priority jobs) and highlight milestones (points where you’ll have something specific to show off).

Once you have this ordered list of jobs, lay them out into separate sprints, totaling the number of story points you think the team can achieve during that sprint.

N.B. to adjust for team size, the time of year (e.g. holiday season), and to leave a % for emergent scope: between 20 and 40%, depending on how confident you are that the stories are comprehensive.

Managing ongoing development

Scope is variable. The plan isn’t fixed – it’s an overall route map.

Estimates are fixed. Once an estimate has been made, don’t change it. Retroactively changing estimates wastes time, and disrupts your statistics.
If you aren’t able to get through as much work as you expected, you need to have this recorded in the sprint burn-down. Reflect on this in the sprint retrospective. Re-project your velocity as required.

New stories are sized with reference to existing stories. This makes it quicker to estimate new jobs, as you can compare them to other similar jobs already completed. So estimation becomes easier and quicker over time.

Update your burn-up chart each sprint.Track the speed to the target (velocity) and the distance from the target (scope).

Once your team is established, use their measured velocity and use this to re-project timings. This is more useful than the estimated capacity that you use when planning with a new team.

Agile Foundation – some key insights from the BCS course

In May this year I obtained the BCS Agile Foundation certification. Here are some of the key insights.

Project variables

In a digital project, you have a set of variables that you can control.


In a Waterfall project, you attempt to deliver a fixed scope. To meet this, the time and cost may have to change – and the quality may also be undermined.

In an Agile project, you fix the time and cost, but vary the scope. You might deliver less, but the quality is high, costs are controlled, you release on time, and what you do deliver is the most valuable work you could have been doing.

(A lean approach is slightly different. You look at flow rather than time, value rather than cost (if you only focus on cost you might not get a good ROI), and quality rather than scope (deliver less, deliver right).)

Agile focuses on the early delivery of value to the customer

A Waterfall project only generates value at the end of the project. You start off by specifying what you want to build, then you carry out design, then development, then testing, before launch. It is only at this last step that any value is experienced, because this is the first time that a working product is used by the customer.

An Agile project goes through all these stages during each sprint. At the end of each time-bound unit of development, something valuable is released to the customer. This means that value is delivered more quickly than in a Waterfall project.

Agile focuses on frequent delivery of value

Working in short sprints allows you to regularly release valuable software.

In 2010 Etsy re-engineered their backend systems to reduce the time taken between software releases. The aim was to be more responsive to customers. In 2011, Etsy released new software 12,000 times – about 30-40 releases per day. They tested code on a small percentage of the audience, and then ramped this up to 100% if it tested well. This new approach reduced defects on go-live by 90%, as each change was so small that it was very difficult to make mistakes.

Think about how you could make a small, safe change to your business process. This would help with risk management, and with agility.

Agile values emergent solutions

It’s important to plan, but plans always have to change. Our competitive advantage is in how well we respond to change.

Management must provide vision and purpose, so that self-organising teams know the overall direction they should be travelling in, and management must clear out blockers for teams. This is different to command and control, with management closely directing the actions of teams.

We must design for uncertainty and change

The ‘Waterfall’ model of developing software was codified by Royce in 1970. He noted that it is “risky and invites failure”. The waterfall approach assumes a simplicity which does not exist in a complex environment like software development.

When applied to software development, a waterfall approach makes three dangerous foundational assumptions:

Myth Reality
The customer knows what they want We don’t know what we want until we interact with it and see if it works for us or not.
We know how to make the software. Generally developers don’t know how exactly to build the software until they start building.
Nothing changes during the project Understanding and requirements change over time. Barry Boehm found that estimates given at the start of the project could be 4 times too high or 4 times too low. Later estimates are more reliable.

In an uncertain environment, use an empirical approach

Build something -> Measure how well it works -> Learn

Loop through this cycle as rapidly as you can.

Regular delivery allows for the earlier realisation of value, and for learning and customer feedback that can improve the product. This reduces the risk of building the wrong thing.
If you take a single, late delivery approach (as in Waterfall), the risk of not delivering the right product only starts to fall later on when you do UAT or go live. It’s better to deliver regularly, and to focus on high-value and high-risk areas, delivering these early to de-risk the project.

The economic case for Agile vs Waterfall

The Standish Group’s 2002 Chaos Report found that:
– Around 1/3 of projects are never completed.
– For completed projects, 45% of features were never used. So almost half of all time, effort and cost was for no reason.
– 19% of features were rarely used.
– 64% of time/effort/cost was wasted. So you need to focus on value, and you need to validate ideas with customers.

The Cutter Consortium found the following improvements due to the adoption of Agile practices:
– 61% cheaper.
– 24% faster.
– 83% fewer defects.
– 39% smaller teams.
These gains are a result of simplicity – maximising the work not done.

The key learning is: make your products smaller and more focused on the core value.

Report on the delivery of actual value, not on progress through project stages

In traditional project reporting, you monitor progress through different stages of the project. But there’s no value delivered until you go live.

Instead: look at revenue, impact, satisfaction levels, customer calls, organisational KPIs.

A 10 tweet summary of NFP tweetup 30

After a short hiatus, the NFP tweetup has returned – this time held at JustGiving’s offices. Here are ten particularly illuminating tweets from the event:

@LucyCaldicott & @Skipinder set up a Facebook group for fundraising discussion

They’ve found it helpful to extend their network.

Recently I attended an event for digital project managers. Most attendees were definitely not in the charity sector. Hearing quite different perspectives – and different acronyms and terminology – was refreshing and illuminating.

The group set up by @LucyCaldicott & @Skipinder is self-organising and non-hierarchical

Modbods is another recommended self-organising digital community. It’s on Google+ and is focused on community management:

@charlotte_cox worked to move somewhereto_ from charity to self-sustaining social enterprise

They had to work on selling their core offer to customers. Potential customers weren’t actually interested in their core vision/mission, so they had to package things differently.
They’ve boiled their key message down to: “Rent space from us, support creative young people”. (Or, to actually quote their website: “Find and book the perfect space to pursue your ideas and ambitions while giving a young person the chance to pursue theirs.”)

Tips on event social media from @dansmythphoto of @TeenageCancer

Covering a live event on social media doesn’t need to entail incessant posting of content:

Facebook will penalise you for sharing too much similar content.

It’s not always sufficient to just share supporter videos. You need to invest in editing them:

Teenage Cancer Trust re-cut their longer videos to appropriate length for social.
Don’t just cross-post your video on all the different social networks: adapt your content for each.
If you want to share a video on social, make it shorter, and make it work with no sound.

Just Giving’s #poweredbypeople campaign at the London Marathon

Just Giving created fundraisers a personalised page that they could share with their friends. It showed how much they’d raised, and pulled in information on their cause.

“People like presents more than asks.”

Also, snapchat filters are apparently quite cost-effective at the moment, with a good ROI.

Let Them Drown – a 10 tweet summary of the 2016 Edward Said London Lecture, delivered by Naomi Klein

The 2016 Edward W. Said London Lecture was delivered by Naomi Klein at the Royal Festival Hall; entitled “Let Them Drown: The Violence of Othering in a Warming World”. Here’s a short summary of this excellent lecture:

Why should we care about climate change?

Climate change is inherently political. It involves people, power and suffering.

Caring about the environment is not a liberal indulgence. ‘The environment’ isn’t somewhere else – our world is our shared political landscape.

Klein noted that water stress and conflict often correlate: “The brutal landscape of the climate crisis”

Othering and environmental damage go hand-in-hand

Klein identified the pivotal intersection between seeing groups of people as ‘other’ – as inferior and with lesser rights – with environmental damage.

Desire for economic growth is the dominant western value system. The values of indigenous people are seen as less important. So their resources can be exploited without their consent, and their links to the land can be severed.

This ‘othering’ can happen with whole nations, such as Iran, where Orientalism was used to justify the 1953 anti-democratic coup.

And until we recognise stateless people and people fleeing climate change as refugees, we’re failing our fellow humans because we see them as lesser.

What could the future look like?

We shouldn’t just see climate change as caused by a monolithic ‘human nature’. The forces behind climate change – capitalism and environmental destruction – have always been contested.

“Climate change acts as an accelerant for our social ills… but it could be the catalyst for the opposite”

Klein challenged the audience to take a broader view of our lives and their significance. What does it mean to have a good life on this planet?

Klein argued that political and environmental action are inherently bound together. Communities owning and controlling their own renewable energy is an example of the joined-up progress we need.

We can’t just prioritise our own country when thinking about climate change. Doing so is to accept a hierarchy of humanity.

And we can’t just think through the framework of neo-liberal consumer choices. Environmental-political change is bigger than that. You can form coalitions that are bigger than those you’d expect from individual consumer choices alone:

Cognitive Technologies – the real opportunities for business – course notes

In late 2015 I completed an online course on cognitive technology. Here’s a summary of my notes. (NB the course is free to take, and is running again from 14 March to 13 June 2016)

What is AI?

AI is not about machines ‘thinking’ like humans. AI is the theory and development of computer systems able to perform tasks that would usually require human intelligence.
e.g. cognitive (planning, reasoning, learning) and perceptive (recognising speech, understanding text, recognising faces)

“As soon as it works no one calls it AI any more”

We expect AI agents to:

  • operate autonomously
  • perceive their environment
  • persist over time
  • adapt to change

Drivers of change in AI

  • Moore Law – microprocessors are 4 million times more powerful than they were in 1971.
  • Big data – low cost sensors, social media, mobiles, the internet gives us more data; combined with better techniques for working with this data.
  • The internet and cloud computing
  • Improved algorithms


Representing knowledge in a computer, using it to reason and plan automatically.

  1. Rules-based systems: Rules base, inference engine (to apply rules), working memory (contains all the information it has to assess). Best for situations with a small number of variables.
  2. Taxonomy: Helps to organise data into a hierarchy.
  3. Bayesian networks (Bayes nets): Useful for situations in which your confidence about a belief may change as your knowledge changes. They can represent assertions, and degrees of certainty. Can help with diagnosis, reasoning from symptom to cause, or for prediction. Less good when you have lots of variables, or when you want to recalculate the entire network.

Some algorithms used in machine learning:

  • Neutral networks – Good for pattern recognition. e.g. speech recognition. (segment audio signal onto phonemes, then associate phonemes with words in the dictionary; named entity recognition.)
  • Support vector machines – good for classification and regression. Often used for off-the-shelf supervised learning. Straightforward to train and implement, and allow a lot of variables. Helpful for Feature engineering.
  • Ensemble learning – using a collection of different models, and combining the output to obtain a stronger result. IMB Watson used this when playing jeopardy. Better than just using any one method.


Automatically devising a plan of action to achieve goals given a description of the initial state, the desired goal, and the possible actions.
e.g. getting from Times Square to the Bronx Zoo.
Search through possible actions to find a sequence that achieves the goal.
Challenge: managing complexity and computation time: combinatorial explosion.
Replanning is important too, to deal with developing situations.
Applications include: Google navigation, unmanned vehicles, robotics.


Improving performance automatically. Machine learning is the process whereby machines improve their performance without explicit programming. Machines discover patterns, make predictions, and become better over time with exposure to data. This helps in situations where we can’t anticipate all situations, or when we don’t know how to program the solution (e.g. facial recognition)

Types of machine learning:

  1. Supervised learning – learning by example.
    An agent is given pairs of information – input (or a number of inputs) and output.
    This allows the agent to understand how to produce the desired output, even for unknown inputs.
    It’s called supervised learning because we use labelled data to train the model.

    Main tasks: Classification (output is one of a set of discreet values) or Regression (output is a number)

    Applications: Sales forecasting, image recognition, text classification, health.

    Challenges: Acquiring and labelling training data; can be expensive to create data set.

  2. Unsupervised learning – discovering patterns in data even though no specific examples are provided.
    e.g. clustering – given a large set of similar items, discover ways to group them into subsets

    Challenges: algorithm has to determine which attributes should be used to group items; sometimes it’s hard to decide where to place an item.

    Applications: Customer segmentation; Social network analysis; Defining product baskets; Topic analysis; Anomaly detection – e.g. looking for outliers in manufacturing.

  3. Semi-supervised learning – unsupervised learning with human interaction to fine-tune
    e.g. giving feedback on the number of clusters, or suggesting attributes for matching.
  4. Reinforcement learning – learning by trial and error.
    Agent acts in unknown environment, responding to sensory input. Responses shaped using rewards or punishment.
    Agents take into account actions and sequences of actions when associating them with rewards or punishments.
    Works best with closed-loop problems – i.e. ones in which there are no inputs other than those caused by the action of the agent

    Challenges: time consuming with many actions or chains of actions; requires a lot of computing power; trial and error has a cost – e.g. learning how to trade on the stock market, so use it when the costs of trial and error are low.

    Applications: physical control systems e.g. elevators or helicopters, or recovering from damage by learning new ways of walking; in some domains it’s our only option.


The ability to take in information in a human-like way: through speech, text or vision.

  1. 1. Natural language processing (NLP) – software that processes human language.
    e.g. understanding or producing. Break down doc to sentences, then words, which are understood using grammar rules

    Challenges: context is tricky: e.g. “he saw her duck”

    Applications of NLP: summarising documents, translation, extracting info, question answering, writing stories, analysing customer feedback. Medicine and Law

  2. Speech recognition – recognising words, tone and emotion of human speech
    Steps: break wave form into phonemes, then match these to words, then put these into an appropriate sequence.

    Challenge: accents, background noise, homophones, need to work quickly. (I wonder how we could add contextual information to understand the set of phonemes)

    Applications: hands-free writing e.g. medical dictation, controlling devices, computer system control, surveillance,

    Future: mine broadcasts and recordings of human speech.

  3. Computer vision – the ability to identify objects, scenes and activities in images. e.g. face recognition.
    Has to build up from pixels to coloured areas, and then objects.
    Machine learning can be used to train object recognisers. error rate 2010-14 reduced four-fold

    Applications: Handwriting, medical imaging, autonomous driving, surveillance, gesture detection. One useful current application is recognition of where spare spaces are in a car park.

    Future: recognition in video, and events detection. This is hard because of the complexity: connecting recognition over time

Physical interaction

Types of robot:

  1. Manipulators – physically anchored to their workplace
  2. Mobile robots – e.g. drones
  3. Mobile manipulators – e.g. humanoid robots in films

Elements of robotic systems:

  • Mechanical and electrical engineering
  • Machine learning
  • Computer vision
  • Planning
  • Speech recognition
  • Sensors – e.g. range finders, location sensors, proprioceptive sensors (knowledge of own position), force and torque sensors
  • Effectors

Applications of robotics:

  • Manufacturing
  • Agriculture
  • Healthcare
  • Hazardous environments
  • Personal services
  • Entertainment
  • Human augmentation

Uncertainty is a challenge for robotics – e.g. needing to take action based on incomplete information, or dealing with an unexpected environment.

Business applications for cognitive technologies

  1. Product
  2. Process
  3. Insight


Embed cognitive technologies in a product or service to help the end user.
e.g Netflix film predictions, which drive 75% of Netflix usage; Google Now / Siri; predictive text.

How cognitive technologies can improve products:

  1. Convenience
  2. Simplicity
  3. Confidence
  4. Emotion

Questions to help you decide whether to embed cognitive technologies in your product/service:

  • Would people like to use it hands-free?
  • Is your product too complex?
  • Do customers have to make complicated choices to buy your product
  • Would a natural interface help customers bonds with your product?


Embed technology into an organisation’s workflow, to increase speed, efficiency, quality.

Automate internal processes, e.g.:

  • The Hong Kong subway system’s preventative maintenance programme. Scheduled by algorithm.
  • Georgia’s campaign finance commission. Uses handwriting recognition to handle the volume of work.
  • Cincinatti Children’s Hospital. Uses NLP to read freeform clinical notes to find patients who might be eligible for clinical trials. Reduced nurse workload on this area of work by 92%.

Automate expert decisions.
Relieved skilled workers of unskilled tasks.
Automate unskilled work.


Improve decision making by analysing large amounts of data – including unstructured data – to discern patterns or make predictions.
e.g working out someone’s risk of developing metabolic syndrome, and which medical interventions were most likely to improve patient health.

Benefits: better, faster decisions that can improve operating and strategic performance

How to find opportunities: See where you have large or unstructured datasets that haven’t been fully analysed; look for processes where the value of improved performance is high.

How to decide whether and where to incorporate cognitive technologies in your organisation – use the “Three Vs” framework

  1. Viable – e.g. perceptual tasks (involving vision, speech, handwriting, data entry, first tier customer service), analytical classification and predictive (forecasting, document review and summarizing), decision-making tasks (situations where knowledge can be expressed as rules, data-driven decisions), planning and optimisation tasks (e.g. scheduling)
  2. Valuable – where it’s worth applying. Involve business processes with costly labour, where expertise is scarce, where there is a high value in improving performance, or where you can deliver features or experiences that your customers care about.
  3. Vital – may be required if: industry standard levels of performance demand their use: online product recommendation, spam filtering, fraud detection; scalability – e.g. processing handwritten or printed data, analysing large amounts of social media.

The impact of cognitive technologies on work

There’s a debate – will machines take our jobs, or will they increase productivity and growth – and demand for human skills? Tasks requring adaptability, common sense, human interaction, ambiguity and creativity will be beyond the reach of machines for a long time. AI is most likely to replace highly-structured back-office roles that don’t involve many customer interactions.

Risks of automated systems:

  • Not infallible. They may eliminate operational human error, but that doesn’t mean that they’re always right.
  • Humans can lose skills if they don’t practice them
  • Humans are bad at monitoring information that remains constant for long periods of time, which may lead to errors being undetected.
  • Poorly automated systems can undermine worker motivation

Approaches to automation:

  1. Replace – completely replace a human performing a job with a machine
  2. Atomize and automate – break jobs into narrow tasks, and automate as many of these as possible. Humans are still employed, but in more of an oversight/remedial capacity.
  3. Relieve – automate tasks that are dull, dirty or dangerous.
  4. Empower or augment – make workers more effective through technology, e.g. by automating brand-new processes.

Strategic choice for approaching automation:

  • Cost strategy – use technology to cut costs by reducing the workforce, or through reducing errors and rework.
  • Value strategy – use technology to make workers more effective, or reassign workers to higher-value work.

Skills that will probably be desirable in the future:

  • The ability to work with cognitive technologies
  • Hyper-specialisation of skills or knowledge that are unlikely to be automated by computers
  • Empathy, creativity, emotional intelligence

Mobile engagement seminar – Charity Comms

A summary of Charity Comms’ Mobile Engagement seminar, 23 March 2016. I attended via Periscope, and share a few observations on this experience at the end.

In August 2015, OFCOM announced that smartphones are now the most used internet device
“Mobile is not the future – mobile is happening now”

“Where are they now? Probably not in front of a computer…” – Tim O’Donnell, operations director, Precedent

Mobile isn’t just about access to the internet – it’s about location services, and functionality like sending text messages.

“It’s not your sector that sets the benchmark.”

Rising expectations are set by the best experiences. e.g. people pay for coffee or the tube using their phone, so they expect donating or signing up for a fundraising event to be similarly easy or they’ll just leave. (I think there’s also a potential for competitive advantage if you do a better job than other organisations in adopting.)

Mobile is different as a channel and a technology to desktop. People think about, and use it, differently.
Use is often more casual, time poor, and relaxed. Perhaps copy needs to be custom-written for mobile, to be shorter and snappier.

Thinking with your thumbs – catering for your users on the move – Chloe Bryan-Brown, web manager, Coram

Coram’s mobile strategy covers

  1. Design (have clear call-to-action boxes; make forms as easy as possible to complete)
  2. Content (make your content easy to scan. Chunk it.)
  3. User journeys

SafetyNets – innovative support for sex workers via smartphones – Matt Haworth, co-founder, Reason Digital and Hannah Shephard-Lewis, safety outreach digital lead, National Ugly Mugs

Reason Digital worked with National Ugly Mugs to create a decentralised, real-time, location-based information sharing system that sex workers can use to share ‘dodgy punter’ information with other app users nearby. This avoids an organisational bottleneck. People can contact the police if they choose, but they are in control.

A good example of the usefulness of user testing in generating insights that a design team would probably never think of: one user remarked that as the background was white, it would illuminate her face. This would mean that she wouldn’t use the app. So they knew that they had to change the background colour to black, so that use was more discreet.

The Big Pathwatch – crowdsourced data gathering – Daniel Brett-Schneider, head of engagement and Eleanor Bullimore, engagement manager, Ramblers

The Ramblers built an app to generate information on the accessibility and state of repair of the country’s path networks.

Lessons learned building the app:

  1. Give yourself lots of testing time. The app was set to launch on Monday, but limited testing time meant that it wasn’t ready in the app store when they left the office on Friday night.
  2. Check that registration is easy-to-use and that it doesn’t have problems
  3. Location services were faulty

The user base was a challenge:

  • Fewer than 50% of app users were already members of Ramblers. This wasn’t expected. (I wasn’t sure if they’d planned to convert this new audience into members.)
  • Existing members of Ramblers weren’t keen on the app. Most didn’t have smartphones, and often weren’t sold on the idea. I wonder how early on in the project this was known.

Favourite jargon for the day: “onward supporter journey development”.

Attending via Periscope

This was my first periscope event. Here’s what I thought:

  • At the start of the event, there were around 15 people. By the end, there were about 10 people.
  • We lost connection for a few minutes a few times during the afternoon event. Everyone seemed to be re-invited, though, so most stayed in the broadcast.
  • The picture quality was a little grainy, so text on slides had to be large to be legible. Audio quality was quite good.
  • You could share messages with other people watching the periscope broadcast, but they disappeared after a second.
  • There wasn’t really a back-channel, like you’d have on twitter. I was on twitter at the same time and there was more engagement there.
  • Charity Comms did a good job resourcing the periscope feed, reinviting people when there were connection troubles, and scanning for questions to be asked during the in-person question-and-answer sessions. If you are thinking of hosting a periscope session, I’d recommend having someone dedicated to inviting people and handling the logistics.

The DSDM Agile Project Framework for Scrum

I’ve highlighted a few key points from the DSDM Agile Project Framework for Scrum. I’d strongly recommend reading the 2014 White Paper produced by Andrew Craddock, Keith Richards, Dorothy Tudor, Barbara Roberts and Julia Godwin for the DSDM Consortium. Download the 22-page white paper. (DSDM is ‘The Dynamic Systems Development Method’.) The paper provides a useful summary of Scrum and Agile methodologies, and reflects on the integration of more granular sprint-focused methodologies with larger strategic project governance frameworks.

The usefulness of combining Scrum with DSDM

The Agile Project Framework for Scrum “brings together the strength of DSDM at project level and the streamlined simplicity of Scrum at the delivery team level”
Scrum is focused on the product rather than the project, “so more emphasis is placed on incremental release of a product in the context of a product lifecycle than is placed on formally ending development work after an agreed period of time.”


DSDM ‘Foundations’ phase covers the full breadth of the project, but deliberately avoids going into detail. This is very different to the ‘Analysis and Design’ step in a waterfall approach.
The Agile Manifesto values values working software above comprehensive documentation.
The DSDM Agile white paper follows this: “break the illusion of security and stability that comes from document-driven, predictive processes. Specification of every detail of requirements, solution design, plans etc. in documents that get ‘signed off’ by stakeholders before work is allowed to progress is now widely accepted to be both wasteful, in terms of time and effort, and ineffective as the basis of governance and control. AgilePF for Scrum embraces the need for high-level versions of requirements, design and planning artefacts in the early phases of the project to frame development and delivery and to support governance.”

Collaboration over contract negotiation

“Typical commercial contracts assume that a traditional Waterfall process under-pins development and, accordingly, ‘a fixed price for a fixed specification’ is the standard for project contracts. Agile projects emphasise collaboration, and therefore contracts need to reflect this.”
Contracts should be “‘light touch’ and ‘guiding’ rather than being ‘detailed and prescriptive’.” “the Product Backlog may represent a contract, effectively defining the scope of a project. But it is cast at a high level and requires customer collaboration with less formality to flesh out the detail of requirements throughout the iterative development of the solution during the project lifecycle.”


  1. Focus on the business need
  2. Deliver on time
  3. Collaborate
  4. Never compromise quality
  5. Build incrementally on firm foundations
  6. Develop iteratively
  7. Communicate continuously and clearly
  8. Demonstrate control


Traditional approach:
Fixed: Features
Variable: Time, Cost, (in practice) Quality

AgilePF Approach:
Fixed: Time, Cost, Quality
Variable: Features

One of the four project variables must be flexible: “With proper planning, any three of the four project variables can be fixed provided one is allowed to vary.”
Agile PF fixed time, cost and quality and varies the scope of the features delivered.
To reach this point in the foundations phase, “an understanding of the high level features is required, sufficient to provide a sensible estimate for those aspects of the project that are fixed. At the same time, it is normal for a subset of the features to be identified as mandatory.”

Feasibility phase

Quickly established whether the project is likely to be technically feasible and cost effective from a business perspective before proceeding.
“The effort associated with Feasibility should be just enough to decide whether further investigation is justified, or whether the project should be stopped now, as it is unlikely to be viable.”

Plan for organisational/business change

“In the context of a project, the solution will include both the Product (often software) and any associated changes within the business wanting to exploit that product.”

Role of the Project Manager

“Managing an empowered team requires a facilitative style rather than a command and control style. It is usual that the Project Manager takes responsibility throughout the duration of the project. This must include both business and technical delivery aspects of the project, from establishing the foundations of the project through to the deployment of the solution.”

What makes an effective digital donation process?

I’ve made donations to a number of top UK charities. They use these techniques to encourage donations:

  • Promote regular giving
  • Amount shopping lists and user choice
  • Ease of use
  • Images of people
  • Social proof, trust seals, where your money goes
  • Emotional reinforcement
  • Use donations as part of a multi-channel relationship

I’ll now elaborate a little on the processes of Macmillan, Cancer Research UK and charity:water

Macmillan’s single donation process

The Macmillan homepage focuses on people and their stories – each of its sections is lead by a photographed person sharing their story.

The donation ask comes either in the rotating carousel or through the site-wide donation button at the top right of each page.
This provides a clear, route to making a donation for those who want to, but the site as a whole leads with support.

macmillan 1

The donate page:

  • Focuses on people and feelings.
  • Directly addresses the visitor as essential, and asks how much they’d like to give.
    This appeal directly builds on the core Macmillan brand message “so no one has to face cancer alone”
  • Empowers the user with choice – of donation type and amount.
  • Shows, for each of the different donation amounts, how many people are giving the different options. This provides social proof.
  • Prioritises regular giving over single donations, because regular giving is more useful to charities.

Two ideas for how this page might be made even more effective:

  • Reduce the number of options at the top of the page – they may distract the user and reduce their propensity to give.
  • Change some of the accompanying images so that they show people. The image that accompanies the £25 donation features a nurse and a patient or family member smiling at each other. I suspect that this is more compelling than the £50 level which shows a plate of pasta.

Here’s what you see if you choose to make a single donation page:

macmillan 2


macmillan 3

  • From the user’s perspective, the entire process happens on the Macmillan website, and with the Macmillan brand.
  • Emotional reinforcement through the form.
  • Trust seals increase credibility
  • Clear phone number to contact in case of difficulty
  • People can see how far through the process they are.

After the 3d secure step, which I won’t show here, you’re taken to the thank you page:

macmillan 5

The thank-you page:

  • calls you out by name and praises you and your impact.
  • Gives additional actions – sharing through different channels, or campaigning.
  • Isn’t the end of the journey – the user also receives a thank-you email:

macmillan 6

The thank-you email:

  • Gives users a chance to find out more about their donation – which is working to build support or implicitly to upsell.
  • Outlines Macmillan’s offer of support – building a reciprocal relationship.
  • Begins to build a multi-channel digital relationship with the donor.

Cancer Research UK’s single donation process

cancer research uk 0

The Cancer Research UK homepage:

  • Use lots of social proof.
  • Features a clear box for people who have already decided to donate before coming to the site.
  • Incorporates the site-wide donate button.

cancer research uk 0.5

The Cancer Research UK donate page:

  • Uses human pictures
  • Is focused and calm, despite including a range of options. Clearly the different options have been prioritised.
  • Prioritises regular giving.

cancer research uk 1

The single donation form:

  • Subtle attempted upsell to regular donation
  • Empowers visitor with choice about where their money goes – but a simple choice.
  • Gift aid option explained visually.
  • Visitor empowered to choose the easiest payment options that suits them. I chose to pay with paypal.

After taking payment, I then had the opportunity to choose my communications preferences:

cancer research uk 4

I was then taken to the thank-you page:

cancer research uk 5

As with Macmillan, the email thank-you message was used to drive multi-channel digital engagement:

cancer research uk 6

The email shows the difference that your donation makes, but also has secondary actions: taking an exciting quiz on improving lifestlye; an opportunity to get support or to connect; and an invitation to deepen engagement with research.

charity:water’s single donation process

charity water 1

The donate page:

  • Uses powerful visuals, communicating the impact of donations.
  • Reassures you about where your money goes.
  • Is clean and focused.
  • Makes paying incredibly easy

Marvel at the ease of use of the Stripe popup. Why aren’t more charities following the lead of ecommerce and using Stripe?

charity water card 1

The payment form only asks for the bare minimum it needs to take your payment

charity water card 2

charity water card 3

charity water card 4

The thank-you page:

  • is focused, and shows the impact of your donation.
  • upsells to a bigger supporting action – using the principle of consistency.

charity water card 5

The email thank-you leads with an image, and articulates the impact of the cause.

I’d be interested to see this exercise carried out on mobile. How well do the top charities compare?