The late Michigan University management professor, CK Prahalad, is best known for his last, and most famous publication, The fortune at the bottom of the pyramid. But to MBA students, management consultancies, corporate planners, and regular readers of the Harvard Business Review, he is also known for a long and distinguished career in management thought leadership. Identifying and recognizing the Core Competency of corporations is another one of his strategy concepts.
I bring him up because today I want to start my keynote on behalf of the Inequality and Technology opening conference by BankInter Foundation for Innovation with a point he made in a speech given at the Indian School of Business in Hyderabad back in 2009.
The tyranny of dominant logic, he called it. We are all socialized to believe, he said, that developing countries cannot be the source of innovation. And this dominant logic provides the theoretical lens by which we see the world. Developed country managers, consultants, academic researchers, all have been socialized to accept this notion.
Because of this, he said, we have never questioned the premise that innovation flows from the top down to the bottom; or, from the North down to the South; or, from the developed countries to the developing. But, as he pointed out with numerous examples in his speech, this doesn’t actually hold true. And this blinds us from seeing otherwise. We must unlearn, the past, to create the future, he told us.
It is this theoretical lens that forms the foundation for my talk this evening. The tyranny of dominant logic is such that we begin work with hope for change and transformation, without ever pausing to identify or question the assumptions underlying our frames of reference. And so, it colours all our strategies, our product development, our business models, and our perception of innovation.
I have named this tyrant the Systems Monster, and he squats there between our best intentions and highest hopes for the greatest good, and the actual outcome of our actions and strategies.
How often have we heard “It is the system” when we have struggled to make our good intentions manifest themselves in the real world to benefit the unemployed, or the underprivileged? Today’s theme is Inequality and Technology, and how the two dance with each other as they seek to include even while creating conditions that exclude. Let me give an example from the banking sector, since our hosts today are the BankInter Foundation for Innovation.
Our world has changed from that of our parent’s generation* – when stable white collar middle class jobs with a regular salary of a predictable amount permitted the evolution of a quality of life through the acquisition of homes, consumer goods, and a secure future supported by our taxes was not only a desirable vision, but a viable and feasible one. (Perhaps I speak too much from the Finnish/Nordic perspective, I hope you’ll forgive me here).
Today, we know that the vast majority of young people cannot expect such a job waiting for them when they graduate. This is as true in Finland or Spain as it is in Kenya or Uganda. It is the internet, and the myriads of opportunities created by the ever increasing reach of communications technology – all in the small device in your hand – that are providing the income streams that people rely on to manage their household expenses. Often, these are from a variety of sources rather than one single paycheck, and, as we can see from the way the Ubers and the AirBnBs are operating, these incomes are not predictable amounts that show up in your bank account on a regular cycle. Added to these changes in the form and structure of employment opportunities (or the lack thereof) are the very real global economic changes as well.
In fact, the main characteristics of our emerging economies are very similar to those seen in what is called the “informal economy” prevalent in the developing countries like Kenya or India. People manage their household finances on irregular, and unpredictable cash flows from a variety of sources. This means that they cannot plan in quite the same way that someone on a predictable, regular salary can.
Yet, the system, that is the processes and structures of the formal financial institutions such as banks, is designed around the predictable – the regular amount of salary that shows up every week or month, and the stable – this paycheck is from one source, an established and known employer such as a big company or the government. This predictability and stability allows the bank to take the risk of issuing loans and mortgages for short terms and longer durations, secure in the knowledge that the amount will be repaid on a regular, predictable, calender cycle – 500e every month plus interest for the next 15 years.
Now if a young couple today, where one person might be a fulltime Uber driver while the other might be a freelance mobile app developer and a DJ a night were to go to the same bank for a loan to buy a house, what do you imagine would happen?
The systems monster will wake up and sit there in teh middle of the conversation between these young people and the bank’s customer representatives – yes, we really want to help you buy your first house, senora, but you see you cannot tell me what your monthly income is. Of course you can purchase this car, senor, but you have no salary slips from Uber to show me.
The system itself is the barrier to inclusion even as it seeks new customers.
On the other hand, and this is where we can see Prahalad’s tyranny of dominant logic in play – there are any number of new financial tools being introduced for the Kenyan market where the mobile phone is the first and primary device for accessing the internet and new technologies. These loan products are all at the early stage of a new market being created and so each startup or company seeks their own solution to the problem of a cash intensive informal sector that provides the majority of the population with employment, and irregular unpredictable cash flows.
Some, like banks and telcos, are using mobile usage data to score for creditworthiness – mShwari is one such product offered by local banks in partnership with the main mobile service provider. Others use a combination of your profile on FaceBook along with your pattern of repayment on small initial loans before offering you larger amounts. Uber uses the driver’s ratings to offer loans for new cars through a bank partnership. Still others, like mKopa, have built up a customer database of payments for their SIM card enabled solar power system for the home to offer a wider variety of consumer durables such as televisions and smartphones, all which can be paid for in small amounts sent by sms – mPesa- to their set top box.
All of these are alternate solutions to the systems design problem of how to create a bridge between the structures and predictable stability of the formal economy, and the uncertainty and risk of the informal – the best known business model that provides the requisite flexibility, negotiability, and reciprocity that peer to peer cooperative economies need is the prepaid plans offered for your phone’s voice and data – airtime minutes can be purchased in advance, for an amount of your choice, as frequently as you please. This hands over control of the financial management to the customer rather than receiving a bill on a calender date for an unknown amount due on a deadline.
The system is negotiable, and does not impose control over the customer’s expenditure planning.
Bringing this story back to the theme today of Inequality and Technology, I will use it to point out to you that the positive or negative impact of the technologies we hope will create inclusive, sustainable societies is very much in our control at the outset if we pause to consider the assumptions being made even as we design the systems and programmes that underly the applications of the technologies.
That can be as simple (even if the solution might not be) as considering whether the target audience for a technological solution can read the language being used – a common complaint from the underprivileged in some way receiving wellmeaning humanitarian assistance by the way of the internet when the cost of data might be as high as USD 5 per GB in a location where most live on $2 a day.
Or, it might be as complex as recognizing that the characteristics of our economies have changed from the predictable and the stable to the social and reciprocal and so our financial systems must now become more flexible and negotiable.
I don’t need to tell you that our future will become ever more dependent on the algorithms that drive big data or automation of intelligence and ever “smarter” tools – if we don’t pause now to consider the underlying assumptions for the design of these systems, or look for the biases that we’re perpetuating, then the inequalities that make up the digital divide are only going to get much worse.
To provoke your thoughtful reflection on this, I will end with a very recent example – Facebook now permits advertisers to choose the ethnic background of the audience that will see their messaging. I didn’t think that was too big of a problem, after all why should I mind if I am seeing far less advertising :) But someone pointed out to me that it also meant that I might not be shown job ads or house rentals if I wasn’t the right colour. This captures everything that can go wrong when we mash up all the megatrends around economy, society, and technology today and consider them from the perspective of inequality and inclusiveness.