Innovation is about executing new ideas and converting them into successful business activities. Creativity is about generating the new ideas with which to innovate. It is an innovation pre-requisite, one that is often overlooked in many businesses.
Innovation is now an emerging strategic need for businesses. Many need to innovate more frequently and successfully. This growing need for innovation increases the demand for more frequent and successful creative thinking to feed innovation processes. Businesses that will be able to create on-demand will be more likely to innovate regularly and successfully during the fourth industrial revolution. One means of delivering this more frequent, on-demand creative thinking, is a new form of digital tools that explicitly supports creative thinking by business employees.
Unpicking creativity
Creativity is the ability to produce work that is both novel, i.e. original and unexpected, and appropriate, i.e. useful [10]. A creative outcome should have value for some purpose, and be novel. This requirement for novelty is unsurprising and on the surface, simple. However, defining novelty, and hence creativity more precisely can be challenging. Novelty is relative, but an outcome is novel relative to what? Is an idea new to a whole sector, or just to the people in one team in a single organisation?
Work by Kauffman & Beghetto [4] sought to unpick these different forms of novelty and hence creativity. It distinguished Big-C creativity, characterised by clear-cut eminent contributions to society, from little-c creativity exhibited in the everyday activities of people, many of whom are non-experts, and generate outcomes rarely perceived to be creative. Between these two extreme forms of creativity, it identified a third form, called Pro-C creativity, which described professional-level expertise, sometimes in non-creative fields, which does not achieve Big-C.
In the field of journalism, for example, if a journalist creates a published article that reports a new story that the journalist was paid to create, then the creation of the article is an example of Pro-C creativity. By contrast, if the same journalist discovers a new person to interview as part of the creation of that article, then the discovery of the person is an episode of little-c creativity.
In my experience, most business employees who undertake creative work exhibit episodes of little-c creativity that, when aggregated, contribute to less frequent periods of Pro-C creativity. Businesses rarely seek Big-C creativity. Framing the new forms of creative thinking that businesses need to innovate defines the new types of digital creativity support that businesses need.
Creativity in business
Support for creativity in business is not new. Creative thinking methods such as CPS [9] and Synectic [3] have been available to businesses since the 1960s. Some of their principles and techniques are now found in design thinking approaches that businesses use to co-create new products and services.
However, these methods have limitations. Most require professional facilitation and preparation - skills and resources that are scarce in most organisations and hence are not accessible to all. Many assume collaborative group-work that needs to be coordinated - coordination that reduces the opportunities to adopt them. Most do not access or exploit the substantial information assets that businesses have, such as strategic plans, market analysis and design documents.
Digital technologies to deliver creativity on-demand for all
New digital technologies are one means of creating on-demand - the new ideas needed to feed more regular and successful innovation. Artificial Intelligence algorithms are a potential game-changer for delivering creativity in business. However, although many data analytic and machine learning technologies now exist, few explicitly support human creativity, or can be applied quickly to discover new ideas from most business information assets. The problem is more acute for small and medium-sized enterprises.
I argue that businesses and their employees need new few forms of digital creativity support. Support to augment the creative capabilities of employees who lack the skills or resources for creative thinking. Support to enable employees to be more creative individually, rather than in coordinated teams and support that manipulates and generates creative content from the diverse forms of existing information asset available in most businesses. Assets such as news publications, public reports, white papers, strategy documents, market assessments and design specifications.
Moreover, I argue that this support can embed automated algorithms to undertake some aspects of creative work more effectively than employees. Recent advances in computational natural language processing and sense-making technologies mean that written content is the new big data - big information than is richer in context and more accessible. As a consequence, these algorithms can search information sources, discover ideas and document these ideas more quickly. They can manipulate information to discover potential creative opportunities, trends and gaps. They can combine information extracted from different sources most efficiently and generate candidate ideas without the cognitive and group biases that many people exhibit. New interactive digital tools that implement these algorithms can become collaborative creative partners, automating and facilitating the use of existing, well-established creative thinking techniques, and empowering their users with new creative skills and insights.
For example, the JECT.AI product was designed to support journalist creative thinking. It invokes creative search algorithms designed to burst filter bubbles. Each of these algorithms discovers different novel content in 10s of millions of existing news and scientific publications. Other journalists interact with JECT.AI to augment their creative thinking about new angles based on this novel content. The image below shows an example of the information and guidance that JECT.AI presents to augment the creative skills and intelligence of a journalist writing about stock markets and the price of gold. JECT.AI also invokes other algorithms that discover creative opportunities, for example, differences and hence opportunities between news stories on one topic written in different languages.
