Category Archives: Innovation

TEDx Reset – Why Robots Need To Dream

Peter Fossick, of Factotum was recently invited to talk at TEDx Reset about ‘Why Robots Need to Dream’.

We’ve posted a link to the video here, in which Peter talks about the selling of technology of Utopian futures that often have social, economic and cultural impacts that favour the few while penalising not only the majority of people but the environment as well. Peter argues that this is the result of new technology but rather the principles, ethics and practices of modern neo-liberal capitalism.

If you enjoy the video you can catch Peter at UX Istanbul in February where as a guest speaker he’ll be talking about DesignOps.

DevOps meet DesignOps

Factotum’s Pete Fossick recently spoke at the Service Design Global Conference in Madrid where he discussed service design, agility and the emergent field of design operations (DesignOps or DesOps) and how they are part Design 4.0 – an emerging approach to designing for Industry 4.0.

A brief history of design… Design 1.0 was paper and pen, using physical tools like a ruler featuring a human agent. Design 2.0 was computer assisted design (CAD) featuring applications driven by a human agent. Design 3.0 was assisted design using CAD apps where knowledge based systems learn from the human actor. Design 4.0 is fully autonomous or semi autonomous design that may or may not involve a human actor (a designer, developer or product owner).

Design 4.0 is an approach to design that marries design for transformation and advanced technologies to deliver innovative and breakthrough products and services for the outcome economy. My talk seemed to resonate with a large number of attendees and there is a sense that there is a shift underway in the practices and approaches we need to use in an agile world informed by huge quantities of data that involves people-to-people, people-to-machine and machine-to-machine interactions.

Design 4.0 marries BizOps, DevOps and the emerging field of Design Operations (or Design Ops) to support design that features semi-autonomous and fully autonomous computer systems (machine learning). While Design 4.0 as a term has been used in different ways to describe design that is focused on social innovation (GK Van Patter, 2009), my definition extends the application of design as a transformation practice to include business thinking and Dev Ops thinking where machine learning and assistive technologies support and inform the design and transformation process.

The conclusion of a new Government-commissioned report by a group representing some of the UK’s top companies, led by Siemens UK and Professor Juergen Maier indicates that robotics, autonomous systems, artificial intelligence and cutting-edge technologies in IoT can deliver huge benefits where Government and industry co-operate and may be able to create 175,000 new manufacturing jobs and generate an extra £455bn in GDP in the UK.

Service, experience, interaction and visual design as a set of practices offer strategic and tactical approaches to designing products and services that are proving highly effective in a world that is undergoing a digital transformation. Coupled with Design Thinking and Human Centred Design they have utilised contextual research and participatory work with users, employees and customers as part of a collaborative design process to gather both qualitative and quantitative data undertaken in an iterative and phased process. However, design thinking (Rolf Faste et al) as an approach has its origins in the 1980s as set practices that are essentially analogue in nature and are both people and time intensive.

However, increasingly design is informed with data-derived insights using advancing data collection techniques and processed using increasingly ubiquitous machine learning and cognitive computing applications. A traditional phased design model or lean approach is not always fast enough or efficient in an agile world where bespoke services and user experiences can be configured in an instant to match a users preferences, behaviours and location and their unique circumstances.

For companies to compete in the Outcome Economy as a part of industry 4.0 requires a new model; Design 4.0, that will increasingly feature machine intelligence and a data informed driven strategy that features data garnered using people-to-people, people-to-machine and machine-to-machine interactions. More on this in the coming weeks and months!

Factotum’s Pete Fossick Talks ‘Service Design’

In the latest issue of Touchpoint, Editor-in-Chief Jesse Grimes caught up with me to learn about the opportunities afforded to me as a service designer and to hear my thoughts on where service design education should be heading.  As the Service Design Program Director at IBM and the founder of the IXSD Academy in London, I have a background that includes developing ground-breaking curriculum in design as well as over twenty years working with start-ups, SMEs, and corporations using service design and design thinking to deliver disruptive innovation.

“In the future designers will need to be polymorphs and trans-disciplinary, where they can adapt to a fast paced changing world. I would like to see a Polytechnic approach in higher education; the University system in the UK is broken in parts and it’s failing its students”
I recently established the IXSD Academy to provide coaching, training and education that has a focus on collaborative and co-creative approaches to develop skills and thought leadership in design, innovation and transformation in the digital economy.

I have been at the forefront of shifting approaches to design education since working with Prof. Norman McNally at Glasgow School of Art in the early 1990s and over the decades I have been involved in developing innovative and ground breaking curriculum in design thinking and pioneering service education in the USA. Check out what I have to say in the SDN’s Touchpoint Vol 9 Edition 1 ‘Education and Capacity Building

https://www.service-design-network.org/touchpoint/touchpoint-9-1-education-and-capacity-building/pete-fossick

Waterfall, Agile and Wagile

In the past two years here at Factotum we have started to use a leaner design and implementation process as part of an integrated strategic design and innovation methodology that is referred to as WAgile.

In the past there was a focus on phased approaches to design and implementation called Waterfall, where the phases of research, framing, insights, design and implementation were completed in sequence – this was typified in engineering, product design and software development.

Then Agile came along and the emphasis shifted to implementation through sprints and a series of ‘drops’ as the software or app  scaled from a minimal viable product (MVP). This works well for software products or new app development but it sometimes fails to include a research and insights process that identifies and engages with target users to understand core needs and how the app is a touchpoint in a larger and distributed service ecology.

Both Waterfall and Agile have strengths, weaknesses and their own merits, but used separately they are limited and flawed.

Wagile

HCD & Contextual Research

Understanding users needs and importantly their desires is key.  Increasingly  ‘wants’ rather than ‘needs’ motivate customers.  For example, customers ‘need’ to text messages but they ‘want’ an iPhone. Customers want a great experience and the social cache of owning a premium brand and awesome products. In short cusotmers are seeking self-actualisation and they are willing pay a premium for it.

To understand ‘wants’ and ‘desires’ we need to intimately know and understand our customers; their attitudes and values. To do this we need to undertake sustained research at the beginning and throughout the early phases of a project through ‘conversations’. However, we need to work quickly and with agility, without over committing resource to design directions that might fail in the market place. 

This is where WAgile becomes attractive.  It takes the best features and benefits of Waterfall and Agile to combine them with HCD and Design Thinking. WAgile is an iterative design and innovation model that employs contextual research driven insights, design thinking, business science and uses sprints to work with agility in cross-functional teams to implement quickly.

At the beginning of the WAgile process I use both contextual inquiry techniques and data analytics to discover who is the ‘customer’ and what are their desires, needs and goals. I balance this with the business needs as we seek new opportunities to disrupt.

This means working closely and dialoging continually with current and potential customers. The process starts with Contextual Inquiry (CI) using ethnographic research augmented with data driven strategies where we use data garnered from customer interactions through owned, paid and social media. Each point of contact with the customer is an opportunity to harvest information and data to gain insights.

User Stories – a common currency

An important tool in the WAgile process are User Stories; the common currency of design. We describe customers tasks and goals through user stories that in turn become features and functions to design and build.

Framing the problem, defining the opportunity areas and designing solutions are based on User Stories. Then workstreams and sprints are forumlated based on MoSCoW principles working with users and the core team. This is part of the continual dialogue and conversation model with customers.

Working sometimes only a day or two ahead of the software developers, the designers use ‘Evidencing’ to bring concepts to life. Evidencing involves creating objects or ‘props’ to act out scenarios and create Rapid Experience Prototypes.  The prototypes explore the way a proposed MVP and design concept will feel and perform. 

By ‘Evidencing’ concepts we can animate and interact with concepts to assess their usefulness in an iterative process with users. This results in tangible evidence (as wells as stills and videos) that enables the core team make early informed judgments about the implications of the design concept.

Based on the outcomes and insights of Evidencing, the user stories are refined and translated into detailed features and specs. The information architectures are refined, wireframes are created, GUI assets are created and coding begins.

WAgile is fast, efficient and enables the user to be involved while the team implements what the user wants.

 

Apple expects to sell 5 million to 6 million iPhones worldwide this weekend!

From Mashable – Analysts believe Apple may sell more iPhones during launch weekend this year than in 2012, but not by much.

Gene Munster, an analyst with Piper Jaffray, expects Apple to sell 5 million to 6 million iPhones worldwide through Sunday, according to an investor note obtained by Mashable. Munster expects that Apple will sell about 2.5 million iPhone 5S devices and about 3 million iPhone 5C devices, with pre-orders accounting for 1 million of the latter.

“We believe that Apple will likely sell all of the 5Ses they will produce for launch weekend,” Munster wrote in the note. “Based on Apple not taking online pre-orders for the 5S, which we believe was to avoid customers immediately seeing delivery times for 2+ weeks out, we believe the 5S is more production-constrained than the iPhone 5 was at launch, likely due to the addition of the finger print technology.”