Twelve years ago, in 2006, Time magazine made an interesting move in deciding on its “Person of the Year.” Instead of one of the many eminent scientists, world leaders, or stars of stage and screen who had influenced the world that year, Time chose to recognise a social phenomenon. It referenced the rise of Web 2.0, with its huge volume of user-generated content, including blogs, social media, reviews of products and sites such as Wikipedia.
‘You. Yes, you.’
Time, in fact, designated the Person of the Year as “you.” The cover of the magazine showed a mirrored computer screen so that readers would see their own faces. The strapline read, “You. Yes, you. You control the Information Age. Welcome to your world.” There were, of course, many who dismissed this as a gimmick. However, Time was right: Web 2.0 has grown and grown. By 2010, if Facebook had been a country, it would have been the third-most populated in the world, and it is still growing.
This also means that as customers, we are increasingly empowered, and demand to be treated as individuals. Time saw “you” as a kind of all-embracing concept that contributed to websites, commented, uploaded content and wrote blogs. In the article discussing Person of the Year, there is no sense in which “you” could be distinguished as an individual: a person with unique wants and needs, and whose wants and needs, more crucially, could be identified from what they did and how they behaved, both online and off. However, this is now very much the case.
To ensure that customers can be treated as individuals, organizations have moved to try to harness data and analytics to support decision making. There is, however, a gap between potential and reality that can be put down to one source: people. The you (we) who are customers are also employees, decision-makers, influencers, teachers and so on.
Reimagining skills and roles in an AI era
We are, unfortunately, creatures of habit. We like to keep doing things the same way. This happens in analytics too. We keep doing what we were doing and leave “new ways” to the data science team. If organizations are to fully embrace analytics, however, this has to change. We all have to play our parts in ensuring that analytics and algorithms can help us to do things differently. Transformation depends on each of us asking questions, learning about new possibilities and taking control of integrating analytics into everything we do.
Realising the full potential of analytics will increasingly mean innovating on small issues like individual workflow and minor elements of customer experience. We all, therefore, need to learn how to think differently, to rethink risk, and learn when to act. We need to help customers discover their own ability to forecast what’s on the horizon, and also how to create their own preferred future today, in the present. We believe that analytics-driven innovation will manifest in the hands of every single one of us.
I believe that innovators are chiefly characterised by thinking in childlike terms. This needs to translate in all of us into an insatiable appetite for new information. Curiosity reveals new options even at dead ends and inspires a sense of purpose and meaning. The missing link is to empower all employees to tap into their inner child or innovator. For too long, we have put boundaries around innovation; only those in labs or with the title may innovate. This is no longer sustainable. Every employee must be encouraged to find opportunities to innovate and create business value. This is especially important because curiosity may be the biggest difference between man and machine in the AI era. Our human empathy and creativity, born out of curiosity, will define our future value.
What will it take to Innovate at Scale? How will the data-driven discovery experience be enabled? Who should drive monetization opportunities? What role will skills and tools play? How will future business models be designed? Be part of our expert study, and discover better practices together with your peers. Express your interest here.
Learning to learn
What this will mean in practice is that we will all need a lot of help from each other and a healthy appetite for learning. Attitudes and business models need to change. Since the industrial revolution, we have expected business planning to run in annual cycles, and defined performance reviews the same way. Networked organisations will move faster, and that means that friction from traditional models from the last century needs to be stripped away.
We will need to use social channels to learn efficiently from each other, and storytelling will accelerate the wheels of knowledge development. Different industries will learn from each other, and maybe even form ecosystems with previously unimagined partner organisations. People in more flexible and empowered teams will indeed define the future.
We also conducted a SASChat - Innovation@scale on Nov 14. See what participants were talking about. We asked five questions. Find an excerpt of that amazing discussion on twitter:
How is analytics changing the scope of #innovation?
(1) As #innovation is all about changing the way of doing things, Analytics can bring a new dimension of being able to predict what results your innovation efforts will bring (Andreas Kitsios).
(2) I think #analytics is building the scope of #innovation more than changing it. (GorkemSevik)
What is the role of scalable analytics capability in driving #innovation at scale?
(1) #Analytics at scale can support decision-makers in finding hidden patterns in tons of data. It wouldn't be possible in any other way (Federica Ballerini).
(2) To enable your business to have exponential growth ability (Igor Dsiaduki).
How has analytics helped athletes collaborate more effectively with their support teams?
(1) Support teams want to know how an athlete's body and mind are progressing, responding to training and competition and recovering. Analytics may not provide the answer but it allows support staff to start the conversation needed for collaboration and build trust (Reece Clifford).
(2) Absolutely. Things like sleep can be monitored if all parties happy, so that what's happening elsewhere (away from training venue) can help create a clearer picture of the athlete's state of mind and body. After all, the 2 are interlinked! (David Smith).