Simple Solutions

On airlines, business class customers can often eat at the time of their choosing. Not so in economy class, where customers are usually at the mercy of the meal trolley. On long haul overnight flights this can be an acute problem. Customers are often asleep at mealtime and flight attendants face the choice of waking up a potentially grumpy customer or skipping a sleeping one only to have to deal with meal requests at later inconvenient times.

Etihad Airways has devised an elegant solution, grounded in simplicity. The sleeping mask now supplied to economy customers is reversible, printed with "Do not disturb" on one side and "Wake me up for meals" on the other. Problem solved. Great usability at low cost.

Sometimes innovation is right in front of you. The solution to a problem can be easy, it's just that no-one has thought of it before.

Don't Be Evil

Many of you will have heard that loyalty card data can be a predictor of epidemic and illness.
There is also research to show that Twitter can be used to chart the spread of disease and the emergent trends of a virus. Now the growth in wearable technology promises a rich source of data to be mined. Google is eyeing this carefully. Buoyed by the success of its flu trends, Larry Page recently claimed that Google could save 100,000 lives per year with access to healthcare data.

Wearables are already providing behavioural and core body function data. So what could Google do if they had access to the data from wearables - not only the data from their own products such as the Google Watch and Glasses but also from third party fitness trackers and cardiac monitors? And what if this data could be combined further to include loyalty card data and patient medical data? The
impact would be potentially paradigm-shifting.

Such would be the knowledge and insight gained from the slicing and dicing of the data, we could treat the healthy, not just the sick. We could predict population trends in disease early and tailor personalised solutions proactively with such speed that patients had treatment options before they even knew they were at risk. We could feed valuable focused data into research that progresses finding solutions to a wide range of medical problems.

So should Google be doing this? Of course they should. No other organisation on this planet has the capacity, access or processes to capture and make sense out of the gigantic data. There are very genuine concerns around data privacy and data transfer. But the benefits to humanity in terms of clinical efficacy, disease eradication and affordable healthcare for all must outweigh the fear and spur us to find new models and frameworks for the likes of Google to operate in.

Google like any multinational corporate will do what they need to do to increase value for their shareholders. This includes playing off the tax systems of nation states against each other. So we get the not uncommon situation of Google earning $18 billion in the UK over a five year period but only paying $16 million in tax. As long as governments continue to look inward, this will not change. But there are ways for Google to contribute.

Googles IPO stated "Don’t be evil. We believe strongly that in the long term, we will be better served — as shareholders and in all other ways — by a company that does good things for the world even if we forgo some short term gains". Over the coming years they will have an opportunity to put this in action.  They need not sell our intimate personal health data to insurance companies. They need not remarket remedies to us based on our symptoms. They could just provide the world with the data we need, no strings attached.

Five Key Customer Data Sets

I attended an IDM knowledge and networking event recently to listen to Edwina Dunn. Edwina and her husband Clive were among the pioneers in making sense of big data. Most notable among their successes were the loyalty schemes for Tesco in the UK and Kroger in the US.

We know that both B2C and B2B businesses have increasing volumes of customer data available to them. While many of these data sets are useful when layered with each other, most are of limited use. However there are some key types of data that are very useful.

Edwina pointed to five types of customer data that are inherently useful: retail data, population data, mobile usage data, credit card data, and social media data. Each of these brings unique features and rich insights to business. When used together, these datasets can reveal opportunity and provide strong direction. 

Still wondering why Facebook acquired What's App? They have married social media data and mobile usage data, two of these key five data sets. With the International Telecommunications Union reporting that 5.2 billion of the world's 6.8 billion mobile phones are in the developing world, this is a powerful combination, reinforcing Facebook's position as the leader in social media with potential to grow further, particularly in Africa and Asia.