Do CEOs of NGOs or social enterprises take advice from McKinsey?
Not blindly, I would hope. They are in bed with the wrong guys too often. However, they do hire quite smart people, who then gather valuable experience. I came across an example, where Tamim Saleh, senior partner at McKinsey, discusses AI from the perspective of a CEO who decides to start their organisation on a path towards AI.
Of course, not everything that excites Saleh about what AI and business would excite the CEO of an NGO or social enterprises. Highly personalised customer profiling or automated call centers are rarely relevant in their sectors. But being a data-driven organisation, which takes advantage of the recent advances in machine learning? Any CEO should listen to what the best practice might be to start going there.
I listened to the interview, forwarded past the commercial AI dreams, and below I distill the most compelling advice for any CEO:
The big picture
AI introduction is coming in three major waves: advanced analytics, automated agents and robotics. We’re right in the first one. This might be why Saleh will from now on only speak of “advanced analytics”, which I appreciate. Maybe even McKinsey senior partners get tired of using “AI” as an unhelpful buzzword. Some pioneers are currently already playing with the second or third wave, but that is not important for the development sector at this time.
An organisation wanting to introduce advanced analytics has three major barriers, none of them being technology: talent, mindset and organisation.
Now – Saleh’s advice for the CEO who decides to embrace AI is as follows.
How to start the journey
- Educate yourself. Spend a day or two with the management team and learn what advanced analytics are. This includes a bit of statistics. Just enough to stop being intimidated and learn to separate truth from hype.
- Identify possible business value. Discuss which changes would really add value to your services or product. This is to make sure you are not following hype or bad advice, but only invest in what serves the vision of your organisation.
- Develop talent. You can buy talent but it’s rare and expensive. It’s imperative to train your staff in-house. Send them to school, hire coaches.
How to shape the organisation
- Have clear roles and concepts – Make sure not everyone in your organisation starts calling themselves “data scientist” or starts spending a lot of time on generating data. Missing clarity would waste resources and frustrate the talented people on staff.
- Do not have one centralised data science team, which handles all of data analytics. This will lead to political friction, as they will always need to convince the departments of their approach.
- Do also not totally decentralise data science. This will lead to inefficient solutions. Each department needs to know what they are doing and have someone with data skills in their team, but some well-defined people in the organisation (or even outside) need to set the standard of how data science is approached (this relates to the first bullet point).
How to involve your CFO
The CFO can play a very interesting role when moving into advanced analytics, though I wager this is more important for larger organisations. With data analytics embraced, the CFO can stop being a data recipient and bookkeeper, and start building an information center around KPIs and forecasts which are of much, much higher quality than before. This enables them to plan the organisation’s resources proactively, completely changing their outlook and massively affecting the organisation.
Our take on this
I think this is actually very useful advice to start this journey successfully. It focuses on value, people and clarity for all stakeholders. On transforming the organisation, not just buying knowledge and hoping for the best.
Of course, all of these factors – value, people and even clarity for stakeholders – are somewhat different in the NGO and social enterprise world. At Seita, this is what we set out to understand and provide. We certainly understand the technology. We also like to think that we are well on our way to learn what impact means in this sector and what makes the people tick who dedicate their professional careers to it.
We’d be excited to discuss your organisations path towards advanced analytics. Or “AI”, if you will 🙂 Please get in touch for a free brainstorming session over coffee!
