Operationalize the ideas of the future with the people you have in the nowBecause it’s in the nature of our work to interact a lot with our clients, reflecting on a year gone by for me is very much colored by the questions of the clients I work with. By far the most frequent question I’ve heard this year was on the topic of growth hacking: ‘Can you help me grow my existing business / online venture / new important business line, by making my organization think (and act) like a start-up would?’
Looking back at 2018: growth hacking as a way to break some taboosTypical start-up worries (‘Can I afford an employee for this? If this doesn’t work, how will I pay the bills? Who can I trust not to steal my idea?’) are typically not what these clients have in mind. But a start-up inspired approach has become synonymous with putting the customer first, high business velocity and smart application of data and new technologies. Now this is something clients have high on their wish-list and were keen to get our help on. At the same time labelling this as ‘thinking like a start-up’ was a good way to get the organization to start doing things that were ‘not done’ before. For example:
- Simplifying team performance metrics. A lot of businesses seem to measure their sophistication by the level of complexity of their performance metrics – simplifying was not on the original to-do list of any of the people I worked with. However, in our opinion less is more if you want your company to start acting in a data-driven way. With these clients we simplified life by introducing two universal KPIs: NPS (happy customers) & Sales (pay the bills) – and made sure that these are the KPIs everybody in the company always knew and worried about. All other (operational) KPIs were still measured and regularly reported on, but in the context of these main two and shared and acted on only by the (few) people for whom they had relevance.
- Working in multi-disciplinary teams to optimize the customer journey. Too often “digital” is considered the expertise of specialists (online marketeers, UX experts) and the assumption is made that specialists need to work in their specialist environment (“no-one would understand them if they explained what they were doing”) – leading to people working in silo’s full of expertise. However, in our experience you will only be a winner in today’s world if you have a relentless focus on the customer need and their journey to buy your product. To identify and remove the existing customer barriers you need the brains of all these people together, bouncing ideas around and testing hypotheses based on data (maybe you need a different product offering, maybe you need different app functionalities, maybe something else). And to be able to do this consistently and effectively you might have to break another taboo, by freely shifting budget between silos, e.g. from Marketing to IT (or vice versa). This got some discussions going to say the least!
- Starting (really) fast (really) small and optimizing in small steps afterwards. We meet many clients with great ideas, that have had these ideas for over a year and since have spent their time holding several customer panels, 200 PowerPoints, a 3-month business planning cycle – but have no market proof to show after this year’s worth of preparations. Meanwhile more often than not some other businesses have started experimenting with the same idea and they have gone from a situation where they could have been an early mover, with all the market share and learning advantages this brings, to being just another player in the pack. ‘Acting like a start-up’ is a good mental framework to get our clients more comfortable with the idea of launching a “MVP” fast, test appetite and refine your proposition and only then start optimizing and make more long-term business cases and design decisions.
We’ve been able to observe clearly this year how reintroducing simplicity along with effective multidisciplinary processes leads to teams that are empowered to take action, have the safety to experiment and be transparent, and are data-driven. These elements are crucial for facilitating short cycles of hypothesis-test-action, but also for obtaining pragmatic ‘proxies’ when the data is not (yet) available. Interestingly enough, organizations that apply these ‘thinking-like-a-startup’ principles at scale become more heavy in their operations (there is more “action”), but less heavy in their management meetings (fewer “great project-plans”). And – dare I say – become more productive & valuable as a result.
2019 will be all about how to make AI workLooking ahead to 2019, I am anticipating follow-up conversations with clients about the role and implementation of AI within their organizations. The challenge with AI is not get the technology; after all, AI is no more than algorithms let loose on data, facilitated by some tooling and computing power, most of which are currently available. Done well this can lead to an automated and self-learning process to solve complex problems like “what is the right price for this product at any given time” or “which landing page will your likelihood to buy”. However, the real question is how to use this technology to create value. Towards customers the question is how this AI can help to better answer their needs and expectations. Toward the organization the question is what it means for the workforce and processes if algorithms take the place of xls spreadsheets. Is this a different way of working for the same people or does it mean there will be a different workforce? And if so – what does the transition look like?
In a way, this challenge bears resemblance to the way in which the frontrunners in ecommerce were grappling with online as a sales channel ten years ago. The challenge with eCommerce wasn’t about how to get the website live, rather how to change the organization around it in order to get business value out of the digital interface.
Winning in a world moving rapidly to ‘online-first’ has proven to be very much about how to operationalize the ideas of the future with the people you have in the now – and I expect 2019 to demonstrate that AI will be no different.
