Updated: Feb 24, 2020
We live in a Data Economy, there is no doubt about it. All leading companies are investing billions of dollars in tech to leverage on Data (more or less ethically). More precisely, most of the top 10 companies today are the ones who invested in it a while ago.
With this video showing the evolution over the last 20 years, you can draw a parallel with the famous sentence "Data is the new oil", as most petro-chemicals companies have been replaced by platforms and tech leaders (exploiting Data very well).
(you should play it with 2x speed)
But with Cambridge Analytica, GDPR and other news, questions about the ethics of those technologies and companies are raised. Most of those groups have more Data than most of us think. Particularly because of their revenue from ads that are tracking all your movement online.
However, this should not continue like this.
Indeed, users/clients and youth particularly are looking for more ethical and engaged companies to work for. They will prefer to buy from responsible organizations while challenging traditional career paths. They want to contribute with organizations to achieve social and environmental change.
There is then no surprise to see giants moving towards more sustainability those days. The social pressure is starting to be felt and if they want to stay relevant tomorrow, they have to act now. For example, Microsoft is having the positive effect of the great Bill and Melinda Gates foundation and just annouced that they will remove their carbon footprint emitted since it has been created (becoming carbon-negative). A good way to lead the movement for those tech leaders and they are not the only ones.
In fact, we are now reaching a tipping-point about sustainability. Climate Change is definitely one of the most famous Sustainable Development Goals (SDGs), being identified as the biggest risk for our world and societies. The media coverage and actions of leaders help to spread the word and the public is taking more actions towards the goal now. For instance, consumers start to understand massively the consequences of their buying power. If you stop ordering food from restaurants that give you only single use plastic forks, they will probably change it (if you tell them), or die...
3 in 4 millennials want to work for a company that matches their values. Salary is not enough anymore!
More companies are understanding the value of respecting global standards as the B Corp certification is providing. They know it is a key element of their future growth (or simply survival).
But organizations leading towards a more responsible activity is just one side of our global change. Some entrepreneurs don't just aim to be responsible, but they also change the sustainable developments gaps deeply through innovative business models with a positive impact from the beginning. We can call them social entrepreneurs.
One of the problems of social enterprises (compared to the B Corp movement for example) is the lack of uniformity between countries.
To make it easy, a social enterprise: 1. has clear social or environmental mission 2. is working towards or already has a self-sustain revenue model 3. is working towards or already has allocated significant resources or profit distribution to fulfill the social or environmental mission The way the profit is shared is as important as the social mission and the revenue generated helps to grow the impact!
The ambitious social entrepreneurs aim to create Zebras and not Unicorns like traditional startups. And we need more zebras, not unicorns. Why? Because Unicorns are mostly looking for valuation nowadays. Raising capital is becoming a goal and not anymore a tool. Zebras, on the contrary, are looking for sustainable prosperity to achieve impact.
Moreover, purpose-driven organizations have a lot of new funding opportunities because of the development of impact investing. The combination of positive change asked by customers, talents and entrepreneurs, supported by funding is a strong signal of change and it is just a beginning.
Given the ongoing diversification of impact investment options and constant growth in a world that’s becoming more conscious of the social and environmental change, further growth would be expected.
Based on the three elements exposed before:
1 - Data is the new oil 2 - Social and environmental consciousness 3 - Zebras opportunities
... trends are clearly identified and already changing our world.
So what can you do as an organization to make sure you survive these rapid and important changes?
Well, to answer this question we need to consider what is the current situation of your organization. Let's take some examples to make it more concrete.
CASE A - Traditional SME
Traditional Small and Medium Enterprises (SMEs) have the highest risk to disappear in the coming years if they do not act quickly. Why? Because most of them did not invest a lot in technology, including Data, they have limited cash flow and resources. Therefore, the Data Literacy level is very low for SMEs.
Wait a minute, Data Literacy? What is that? In simple terms: "speak Data". Otherwise, MIT and Emerson defined it as "the ability to read, work with, analyze and argue with data". (Short Reseach paper)
This case is very important because the "dynamism of small and medium-sized enterprises (SMEs) is critical to the success of the UK economy. Representing over 99% of UK businesses, they provide 60% of private sector jobs and account for almost 50% of all private sector turnover." (London Stock Exchange Group).
Those figures are simply incredible but real; and they show the importance of those organizations in our societies worldwide. According to the World Trade Organization, (World Trade Report 2016 Leveling the Trading Field for SMEs) SMEs represent over 90 per cent of the business population, 60-70% of employment and 55% of GDP in developed economies.
🚀 🚀 🚀 If you are Data Literate and understand the power of storytelling to influence human decision-making, you probably understand why I put this 99% first in bold. Hopefully, it also means you have the necessary curiosity to ask yourself if this number is relevant for other regions and how it has been calculated... 🚀 🚀 🚀
SMEs have the ability to change slightly faster than larger groups and the founders had a meaningful goal when they stared the venture. It makes them the perfect example for the empowerment of Data (often from scratch) to thrive in the future.
This could be a main competitive advantage for the future as
"companies that invest or have data literate cultures are seeing increases of $300-500m in enterprise value"
(SME Solutions group, Inc).
The adoption of Data Literacy is not an easy process because it is linked to the upskilling of existing manpower and hiring top-performers who have the relevant skillset to spread the necessary cultural change. It is simply a transformation that could take time.
When we say Data is the new oil, it means it is the backbone of a lot of innovations. It could be powered by Artificial Intelligence, helping to do repetitive tasks faster and better (by reproducing human behaviors from historical Data) but most importantly and in most cases, organizations should be Data-Informed, taking better actions from insights. (To discover more about the distinction between Data-Informed vs Data-Driven, please check out our short article there)
How to become a Data Literate organization?
1- Start now
There is no need to overthink the strategy for your organization from the beginning. Start small, understand how Data can help you with quick-wins, and build your vision/strategy from those examples.
As all changes within an organization, communication, support from the management and proof of success are key to develop a Data Literacy Culture.
You will need the right resources to start these first Proof of Concepts and we recommend you to work with trusted and experienced partners to start the projects while hiring/training (at least) a "champion" in your organization to manage it and keep the knowledge more easily.
2- Upskill teams
Being Data Literate does not mean to be a Data Specialist. No need to hire a PhD in Data Science to do this job.
However, offer training to your teams to increase their performance because Data Literate people are more often top-performers than others. There is some technical skills needed but most of it is a mindset. The goal is to increase curiosity and deep dive on why things happened, validate it with facts and be able to challenge metrics or graphs.
All tertiary jobs are impacted as most employees have received a spreadsheet or read an article with graphs and numbers before.
Argumentation and validation based on context and understanding of the situation is what matters. Facts and visuals are decisive elements used in decision making but it is also easy to make wrong human decisions if you are not challenging what you see.
3- Measure, Analyze and Act
To be able to make decisions based on facts, you need Data. It is often something we forget but Data Collection, Data Management, Data Architecture, Data Engineering are very important to be able to make decisions. The visualizations and analysis you can do if you have simultaneously great Data and business questions are limitless. It will support the most important decisions as you can track, monitor, understand, predict and act based on this trusted and available information. But without relevant Data there are no relevant Data-Informed actions.
Those 3 points are not exhaustive but they are the priorities you should embrace now if you want to become a Data Literate organization.
To summarize, SMEs should invest in more Data Literacy (and be technology-ready) to make better decisions and innovate further while strengthening their focus on SDGs.
What about large Multi-National Companies (MNCs)?
CASE B - Large MNCs
The speed of change for large MNCs is often slower. More people to empower, more difficult processes to adapt and legacy systems that are costly to change. However, those companies often have more budget for innovation (as they have been successfully profit-driven for years), which makes it easier for them to test with external partners and embrace tech pilots.
Multiple MNCs did big mistakes hiring first talents with strong Data capabilities.
Why? Simply because those highly specialized Data experts are not talking the same language as the business teams and no one is there to bridge the gap. The most important roles to embrace Data Science within MNCs are Analytics translators, helping teams to work together. Another way to make things happen, is to build cross-functional teams with the tech and business people collaborating further to have this translation of business needs into Analytics problems.
Large corporations have the budget to hire top Data talents but they still face the same issue as the SMEs on the Data Literacy. Only the minority of the employees are Data Literate which is a loss of efficiency and performance. Data Literacy could be a good way to retain talents as training provided by large corporations are often a great personal development and open doors for a career evolution within the organization.
All managers and leaders should be Data Literate tomorrow to lead the cultural change that is needed.
However, most of MNCs are facing a second major problem, the branding and real action towards social and environmental responsibility. They need to combine technological and responsible change simultaneously as CSR (Corporate Social Responsibility) has been often on the side of the activity and not in the core of their strategic decisions. As expressed during the introduction, stakeholders and employees are now asking for more.
It is not enough anymore to do Good on the side, it is the overall business activity that is judged nowadays.
Social Intrapreneurship has a big potential to empower change through engaged employees acting like entrepreneurs to develop new solutions in the existing organizations. The new initiatives should be purpose-driven and helping to transform the organization while increasing the retention.
More and more Directors of Sustainability are joining the management teams and being involved in key decisions but it is still not the majority of the groups that are moving fast enough in that direction.
Main decisions should balance profit and positive outcomes for societies (or at least ensure no negative impact).
From the video before, it is possible to envision how fast the change can be in our economies. The organizations leading the top 10 twenty years ago are really different from now, and we can be sure that in 10 years, the leaders will be the ones combining a positive impact (particularly sustainability) and economic growth during the 4th Industrial Revolution.
Which MNC will be able to embrace technology and Sustainable Development Goals together? Impossible to tell it now, but we know the ranking will be on purpose first.
CASE C - Hyper-growth startups (too much tech focused)
I love startups, but I hate startups only playing on the valuation bubble. For instance, 40% of the AI startups are not using AI in OECD... but they raised millions.
It will not continue for long and this is mostly happening in big tech hubs worldwide. The main issue is when you build a product for the product and not for the needs it is tackling.
If you put the "what" over the "why", you lose the innovation focus, particularly when we talk about Sustainable Development Goals.
Those startups have great talents and mostly use the lean methodology that helps to build, measure and adapt quickly to find what is working well before scaling it. They often understand technological opportunities very well and are Data Literate. But when you want to optimize numbers of users with no consideration on your positive impact, you are focusing on the wrong metrics for the future. This is the unicorns vs zebras comparison table shown before and it is clear that this bubble will not be sustainable.
Impact investors are asking for SROI (Social Return On Investment). They are not only looking for profit and tech, and it is a good sign. More startups will focus on what they did well before, but adding more purpose into it if they want to attract more demanding users and investment. One trends re-enforcing this idea is the increasing numbers of investors who are insisting on the fact they will invest based on Environmental, Social and Governance (ESG) criterias. ESG investing refers to a class of investing that is also known as “sustainable investing." (source)
The growing impact investing opportunities are incentivizing companies to be transparent and measure their impact with key indicators.
Ventures focusing on profit and valuation, wishing only a successful exit have a short time to live because in the long run,
as the consciousness is increasing within the pool of users and consumers, startups will have to adapt to the demand.
CASE D - Social Enterprises
Social Enterprises are in most cases SMEs but with a particularity, their beneficiaries. Indeed, they define a target group they want to support (a cause) with their business model.
Their social and environmental mission is strong (often associated to a personal experience) but the lack of empowerment of technology is a bottleneck, even for new ventures.
Too often, they focus on the direct impact forgetting the tools to make it bigger. A lot of social ventures are still not really self-sustainable, relying on limited grants and donations to achieve goals and they have limited human resources.
This budget constraint is the main blocking point for growth and innovation. Data Science and other tech related tasks could be expensive as it is requiring the relevant resources that are really scarce.
That's why it is often not possible for social enterprises to leverage on Data at a professional level.
Some Startups for Good, really aim to be Zebras but we need more of them to lead the way and break the common association of social good with charities only. Actually, too many Social Enterprises are acting like charities, and we should help them to rethink their impact strategy through a more sustainable business model.
Can Data help them to be more sustainable?
Develop more Data Literacy internally and kick-start Data Science projects can help to see the value of empowering a business-driven mindset with the use of technology for a scaled impact. The first use case is impact measurement, which is Data Analytics of impact metrics. The second one is the understanding the clients/beneficiaries with simple visualizations to make better decisions. And once you have more Data Literacy and experts working with you (internally and through external partnerships), you can build on more advanced things to accelerate and scale your activity. It is important to start the Data journey now with low hanging fruits projects and trusted partners.
Data Analytics can help to create a compelling storytelling based on facts, supporting a successful fundraising.
The development of a Data Literacy Culture will help Social Enterprises to thrive and reach the transformational outcome they want to have on our economy with better Data-Informed business decisions.
CASE E - Charities, NGOs and non-profits
The frontier between a social enterprise and a charity is often blurry but this graph coming from a report made by Social Enterprises pioneers (UK) will help to clarify it.
For social enterprises a business-driven mindset (revenue to sustain) with a mission is more important than the optimization of dividends for shareholders.
Charities have (almost) no revenue and rely on donations to sustain an impact. Their most important mission is to fill a gap in a system, often associated to emergencies to protect communities. For example, building education programs after a conflict while the local government is not capable to do so. But part of the mission is also to leave as soon as possible! Indeed, a successful charity is one that has been a capable to find sustainable solutions, making themselves obsolete.
Similarly to social enterprises, the need of technology and Data is often not understood or identified by charities, the direct interactions with beneficiaries taking too much importance in decisions.
As they need to plan a budget (and raise funds based on it) and most of charities leaders do not have Digital Dexterity to embrace Data and Digital as a tool for positive change, it is almost never planned to invest in technology.
Budget constraints are even more important those days as the pure donation model is sometimes replaced by impact investing, limiting the amount available to fund raise. Data Literacy is not yet seen as strategic investment by charities leaders, and we should start the change at this level. Again, the first area charities will use Data for, is to tell their impact stories based on facts. It will help to raise more funds and achieve their goals while monitoring their impact. The pressure put by various stakeholders on transparency (and implicit measurement) should be the first driver of Data initiatives within charities.
As more charities are taking the path, others will understand better how to use Data to support their goals through existing use cases while sharing better stories of impact.
Build the future you want to live in!
Existing organizations could be the leaders of tomorrow, but maybe the future leaders are not existing yet!
If you identify an opportunity that has a social and environmental mission (associated to SDGs), with a sustainable business model empowering technology, you risk to be unstoppable.
New and existing businesses will aim for that as the two main pillars of growth are summarized by the Tech for Good and the underlying Data for Good movements.
Impact can be measured by the breadth and the depth of your actions and technology is a key driver to make it happen at scale (large breadth) while the depth is depending on how far you want / can impact lives and environment with it.
It is not easy to combine both simultaneously but
Zebras do not only exist in Dreams, they are reality, so I am sure you can find a way to make it happen within your existing organization or a new venture.
(potentially with other partners to complement your actions- #SDG17 Partnerships for the goals)
You should start now
Gartner was recently warning companies that they should embrace Data Literacy.
By 2020, 50% of organizations will lack sufficient AI and data literacy skills to achieve business value
Business value is a key word that we should not forget when we think about purpose-driven organizations; as those should be leveraging on revenue to increase their impact.
The Data literacy culture will bring more revenue to Businesses for Good, self-sustaining the positive impact that is shaping a better world for our communities while opening new funding opportunities.
Embrace the Data for Good movement now!
Dathappy is a social enterprise aiming to bring Data Literacy to all (impacting organizations and people).
We are on a mission to bring professional Data Science services to all purpose-driven organizations empowering individuals around the globe that have less opportunities
Because innovation and growth generated through Data projects should be accessible (understood and affordable) to the change-makers shaping a better world and not only profit-driven large corporations.
Because the job opportunities are incredible in the Data economy but some communities do not have access to those. Let's open opportunities to all with an inclusive gig economy
CONTACT US and we will co-create a better future, combining the power of purpose and Data!
We can help you with: - the upskilling of your teams
- the realization of Data Science projects to make better Data-Informed decisions
- the sourcing of the talents needed for your growth (with our continuous support) - the development of your Data Strategy
Thanks for reading,
Founder and CEO of Dathappy
I am always open to discuss social entrepreneurship, sustainable development and tech related innovation so do not hesitate to connect through a coffee, lunch, call. I am also sharing a lot of content related to that on LinkedIn so follow me.