17 MAY 2019
A new economic paradigm is beginning to dawn with emergence of the smart economy, the sharing economy, the circular economy and the platform economy. It is the synergies of these movements which is causing huge social and economic changes in our lives.
Virtually every single business is beginning to transform from an old economic order into a new reality. The digitisation of society and the economy has an impact on everything and everyone. Policy makers and decision makers are roused to the transformational process and impact on businesses.
Smart business emerges when all players involved in achieving a common business goal are coordinated in an online network and use machine-learning technology to efficiently leverage data in real time. These types of technology-enabled models, where most operational decisions are made by machines, allow companies to adapt dynamically to changing market conditions and customer preferences, gaining tremendous competitive advantage over traditional businesses.
Without a second thought people adopt new technology in their daily lives. We have exchanged our landlines for smartphones, adapted to GPS navigation systems in our vehicles, and Wikipedia has conquered the Encyclopedia, much like Google Earth made the Atlas obsolete.
All these technologies integrate online, connecting people like us and with other smart technologies. The common denominator is that they help simplify things, making life more comfortable and budget friendly; these are the first applications of the Internet of Things (IoT) in our homes.
We expect to see 20 billion internet-connected things by 2020. These 'things' are not general-purpose devices, such as smartphones and PCs, but dedicated-function objects, such as vending machines, jet engines, connected cars and a myriad of other examples.
Mark Hung, Vice President, Gartner Research
Source: Gartner Research, 'Leading the IoT'
Ample computing power and limitless digital data are becoming the fuel for machine learning. Data experts create models for specific actions and algorithms churn out data to inform better real-time decisions — these become the basis for business actions. Machine learning is more than a technological innovation, it is replacing human decision making.
To become a smart business, organisations must enable operating decisions to be made by machines fueled by live data rather than by humans supported by data analysis. Take for example the rental business for cars and bikes in Go; live data is used to predict and dispatch bikes to destinations where users reside, which has improved the customer experience and reduced operating costs in comparison to earlier years.
For businesses that want to create smart processes, the first step is to map what decisions are currently made by human decision makers and find ways to replicate the simpler elements of that process using software. However, as Martin Lindstorm says in 'Buyology: Truth and Lies About Why We Buy', this is not always easy as human decisions are often based on common sense or even subconscious neurological activity.
While working on various digital transformation projects for different verticals and consumer segments in Asia-Pacific and US markets, I have come to realise that once a business has its operations online, it will experience the "data deluge". To assimilate, interpret and use data to its advantage, a business must create models and algorithms that optimise product logic and market dynamics. Without the support of machine learning this will not be possible.
In summary, digital-native companies — OLA Cabs, Uber, Flipkart, Amazon, Alibaba etc — have the advantage of being born online and being data ready. Their transformation into a smarter business is a natural progression as they have proven that their model works and has had a transformative effect. It's time for other organisations to understand and apply smarter business logic, which may look technologically intimidating but are more feasible.