Catalina Panoiu

The most gifted leaders and managers I've met excel at identifying individual motivations and matching them to development paths within the organisation, strategy or otherwise. Individual strategies to achieve this differ, but a few commonalities stand out. First, trust and honesty. Clear, transparent communication and absolute respect for the points of view shared are the basis of a good relationship. Without them you cannot expect honest sharing of personal motivations and goals, nor can you share developmental feedback when it is required. Next, genuine care for the others' perspectives and for supporting team members' growth. Remember that a leader is also an inspiration and sometimes a mentor!

Check-ins at both team and individual level are perhaps the most overlooked opportunity to maintain dialogue, identify red flags and support team members. How many of us have been in meetings when check-ins are limited to 'going around the table to check on progress'? Unstructured meetings lead to partial, or at worst misleading feedback, so take the time to structure the agenda, involve team members in collecting topics beforehand, and follow up when needed. Better yet, take the time to see team members regularly to discuss individual projects, share ideas for new initiatives and exchange feedback.

The trickiest or most fun part of it, depending on perspective! :) I agree with Anthony J James, the journey is as important as the destination when it comes to building, maintaining and enriching innovation cultures. In my experience, if there is little vision, inspiration and fun, there will be little to no innovation and drive within an organisation. The term may appear fluffy, but innovative cultures share a drive for continuous improvement, dialogue with internal and external stakeholders, and open experimentation. They require the right conditions - transparency, encouragement to experiment, honest feedback and camaraderie backed by clear development paths for both people and ideas.

Best-in-class companies have well-defined frameworks for idea generation and prioritisation, complete with development tracks and resources. A digital context further supports this structure via Agile and Lean practices. The foundation of any such framework is a well-designed portfolio: specific categories for immediate improvements (likely prioritised by product teams via a time / value matrix), medium-term developments which require diversified skillsets and resources, and longer-term bets. Moonshots remain in a league of their own, for better or worse. In my experience combining ideation methods and sources yields the best results. However, without a strong development framework the best ideation is unlikely to deliver value.

Word of (unsolicited) advice: scaling should be on your mind from the very beginning, with decision criteria built into early experimentation, prototyping and all the way to MVP. First, beachhead strategies. If during the design and development process you've gathered sufficient high-quality data on perceived value and purchasing intentions from several audiences, you should have an informed view on early adopters and effective marketing messages to support your scaling plan. Financial modelling will be next, with profitability expected down the line. If on the other hand no conclusive data emerges - low purchasing intentions, limited perceived value etc. - get ready to kill the project quickly and share lessons transparently.

We seem to be in furious agreement: experiments are not only critical filters during the design and development process, but also eye-openers in terms of perceived value, areas of improvement and high-impact marketing messages. In my experience, the pitfalls awaiting experiment designers are threefold. First, ensure the experiment is designed to challenge, not validate assumptions. Bias is built into all human endeavours, but can be managed via combined validation layers - surveys, A/B tests, focus groups etc. Next, leave room for open questions and experience sharing by your audience. Stay open to surprises. Importantly, set kill and scale criteria early on when experimenting, in order to gather data required for the decision early on.