To be innovative is one of the most highly prized qualities in modern business. For any organisation described as innovative, one would immediately see that business as progressive, challenging, risk-taking, focused on digital transformation, modern and successful.
However, the truth isn’t quite as simple as that. While most businesses might claim to be innovative, for many it is merely smoke and mirrors, a PR exercise that positions that company as innovative without really delivering. Organisations that are serious about being innovative know that it involves a different culture and a different mindset to be successful. And for innovation to be future-proof and sustainable, it is also going to increasingly involve artificial intelligence (AI).
The evolution of innovation
Around a decade ago, with the emergence of agile and digitally-focused start-ups, it became clear that businesses needed to innovate more than ever, in order to be successful and maintain their market position. Traditional businesses were coming under threat from new market entrants, start-ups that were structured in a way that put innovation and fresh thinking at the heart of their operations.
This led to the accelerated emergence of a technology to capture and manage innovation, the idea management platform. The concept had already existed in different forms, but the increased need for innovation in more traditional businesses saw idea management platforms become more mainstream, offering the ability to capture, refine and realise ideas, and allowing discussion and engagement across multiple communities – internal or external, employees or management, national or international.
The last five years has seen this technology evolve even further, as innovation becomes even more highly valued, with the latest idea management platforms making tangible use of AI to power innovation programmes.
Artificial intelligence = sustainable and scalable innovation
While AI has existed as a concept since the mid-’60s, for a long period it seemed as though it was never quite going to push through to the business and technology mainstream. The last few years however, have seen increasing adoption of AI and it is starting to fulfil its undoubted potential and have a real impact on many businesses.
One area where AI has undoubtedly made a difference is in innovation and idea management, adding machine learning capabilities to ensure corporate memories for ideas are much longer, leading to truly sustainable and on-going innovation.
Even when an organisation is using an idea management platform, it is possible for a good idea to be forgotten if it’s submitted at the wrong time. If there isn’t a current need for an idea, then they mostly either drift into the ether or are stored away somewhere, undiscoverable and never used. Using an idea management programme that leverages machine learning algorithms allows the platform to keep building, learning and developing its own memory, which becomes more useful in the future.
Just because an idea in response to a specific request isn’t quite right at that moment, it could be applied to another area of the business at another time. The right machine learning technology can store ideas until such a point that there is a use for them. This means people looking for solutions will be alerted to previously submitted ideas that could work, based on the idea management platform’s understanding of their needs and memory of what has been suggested before. As the volume of ideas grows, it become less efficient or even impossible for people to manually make connections between these ideas, whether they were implemented or rejected. AI tools help solve that problem by highlighting unexpected relationships between ideas.
Retaining the value of good ideas
Similarly, if an organisation is running an innovation challenge across its target audiences, it is possible that it could get thousands of responses. The most immediately relevant ideas will be selected, but many others may be rejected for different reasons, such as lack of resources or poor strategic fit.
Only a small percentage of those ideas are going to be taken forward initially. What happens to the remaining ideas? They will be discarded and potentially forgotten, but often there’s still value to be found from ideas that don’t find a home the first time around and by applying AI to idea management, these initially overlooked or rejected ideas are folded back into the corporate memory, with the knowledge that in the future they may be useful. The platform learns about each idea and holds it there until that time, which might be a week, a year or even a decade in the future.
Businesses must understand that innovating for today is the machine that feeds innovation for tomorrow – culturally, in capability, process, and much more. To do this effectively and to future-proof good ideas, it means adopting AI-enabled idea management to power the next and future waves of innovation.