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  • Writer's pictureJayne Whitton


Over recent years charities have strived to embrace digital ways of working, to increase their effectiveness, efficiency and impact, by emulating the success of commercial organisations that have redefined themselves for a digital age and enjoyed exponential growth.

During this time, I have seen a language and infrastructure develop around digital ways of working based on how organisations such as Google, Amazon, Spotify and Netflix work, that have been enthusiastically embraced by many different charities large and small, as the sector strives to capture the benefits of digital. This is why I wanted to shadow a CEO at a social tech startup to try and learn more about how a digital first organisation works, with the aim of transferring these learnings to my next role as a digital leader.

It was a fascinating experience, I could recognise both similarities and differences in how charities and startups approach digital. But the eureka moment for me was that digital ways of working are all interconnected and therefore the more they are compromised, the more the digital model starts to break down. This makes it much harder for traditional charities to fully realise the benefits of digital, if they do not take a whole organisational approach, which involves significant change. The key differences I observed between a traditional organisation trying to embrace digital ways of working and a purist, digital first organisation were:

  • Mathematical modelling sits at the heart of a digital business, it provides the stable core through which a digital business can test, refine and learn, either in real life or through scenario modelling. It is the development and confidence in the mathematical model that drives growth and informs business decisions and without these complex models at the heart of an organisation, it will fail to effectively transition into a digital world, as it will lack the stable core through which it can learn and grow.

  • Data transparency and data informed decision-making follows on from the mathematical model. It involves universal access to business data, in real time, to help inform decision-making, enabling staff to better understand the organisation and its leadership decisions, whilst also providing a tool for everyone to hold each other to account through the power of data. It moves away from the parent child relationships so many of us have with our employers and enables adult-to-adult conversations to grow.

  • Operational planning and performance management is ambitious at a digital startup, working to a combination of committed must meet targets and wildly ambitious targets designed to stretch the organisation. These OKRs (Objectives and Key Results), are a move away from the rigid KPIs of the public sector, often adopted by charities. They are developed by the whole organisation working together and therefore jointly owned and understood, reviewed weekly and revised quarterly, alongside rolling budgets. They enable an organisation to quickly adapt and reconfigure to meet their targets, underpinning agile working.

  • An obsession in demonstrating “Product Market Fit” which is simply where your offer meets the needs of your target audiences. A simple aspiration, it embraces the complexity of truly understanding your target audiences, identifying an unmet need, developing and refining the offer, by listening to feedback and understanding data to be able to demonstrate that the core offer is not just wanted, but loved. As to build a successful digital organisation you need to build a community that loves what you do and trusts you.

  • People, not technology are the key driver of organisational success in a digital startup much like a management consultancy. This makes good recruitment business critical, which means investing in finding and nurturing the best talent you can find, creating the flexibility to invest in people not defined roles, and to build an organisation around the skills you need right now, where every role adds demonstrable value to a growth agenda.

  • Small, fluid, teams that work effectively together, through agile methodologies, is something many organisations aspire to, but struggle to implement. In its purest form, it represents a shift away from hierarchy where leaders and experienced experts sponsor and drive projects, to an organisation that effectively enables people to come together, solve problems and move projects forward. In this world where teams are empowered through data, devolved decision-making, trust and accountability, there is an ease to challenging targets and multi-disciplinary working.

The world of social tech startups is brutal, where 9 in 10 fail, and success is dependent on demonstrating, constant exponential growth. To this end the focus for digital startups is to: develop a data driven model, scale and execute that model well through hiring and nurturing the right people and monitoring the effectiveness of both the model and its execution, building in the ability to rapidly adapt the model and therefore ways of working, based on data insight. In my experience this is very different to how traditional charities operate.

Some would argue the type of exponential growth synonymous with digital startups is not appropriate in the charity sector, I would argue why not. The world is rapidly changing around us, we need to face into the social problems of today, recognise where traditional ways of tackling them has not worked and look for new and different ways to tackle them. We need to do more than just adopt digital ways of working in discreet projects, we need to demonstrate a hunger to grow our impact, an ambition for exponential growth and scale and a desire for the necessary whole organisational change to deliver it.

As this will now be the key theme for my MSc dissertation I am really interested in other charities experience of digital change, especially where they represent good practice in how traditional charities have changed the way they work, by putting mathematical modelling and data at the heart of the organisation.

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