Love it or hate it, the fact is that data is gold.
As Geoffrey Moore likes to put it, “Without big data, you are blind and deaf and in the middle of a freeway.” And you wouldn’t want to be there, especially when data is fueling businesses in ways more than ever. Qualitative data helps drive businesses in ways more than one. In the hyper-connected world of digital devices and systems, if you are not leveraging data for business, you are lagging the game for no good reason.
In this article, we will discuss how data-powered business models are carving their way into the future.
A data-powered business model is the one where businesses utilize data to improve processes, make better business decisions, offer more personalized customer service, design the revenue model based on data, and/or offer products or services completely dependent on data.
Data-powered business models are different from the ones that use data in order to accomplish a part of the business process. The data-driven business models make active use of data to make decisions in place of emotions or instincts. Every business leader hunts for data-centric insights to improve the business outcomes, and going the data-powered way seems like a wise choice.
Top benefits of having a data-driven business model include:
Businesses that unlock the true potential of data and place it in the center of the business strategy can be truly termed as a data-powered business. Let us have a look at a top few examples of data-powered business models that are future-leaning and future-ready.
Sustainable, environment-friendly, and hyper-connected smart cities are in vogue. Smart cities leverage IoT sensors to collect data from various sources and utilize the data to drive systems within the city. The objectives can be multi-fold, such as improving the energy efficiency and consumption or revamping operations across the city – from traffic management to town planning, waste management, to crime detection. Data can be incremental in planning a smart city for estimating the inflow on public transport, helping to decongest the cities, identifying areas that require more public health penetration with AI-based prediction, and enhancing the overall governance in the city.
Connected cars are cars (and other vehicles like buses) that can connect to the other cards or vehicles on the road enabling other cars to share data via IoT devices. More importantly, connected cars usher in driver safety, security, ease of navigation for a simple day-to-day problem, including finding a parking spot. Connected cars generate extensive data about the car performance, speed, and door locking logs, which make it a heavily data-driven and data-dependent model that is as futuristic as it can get.
OTT media services or video streaming is one of the most rapidly expanding entertainment channels at the moment. The OTT services such as Netflix make active use of customer viewing data to predict customer preferences based on their demographics as well as geographies. Making use of this data, the OTT media service providers can improve the customer experience, offering them exactly what they’d like to view instead of exploring a sea of content and being overwhelmed. Netflix for instance, not only collects viewing data but also the ratings, view times, and user ratings to curate a more customized viewing experience as well as onboarding content types that truly sell.
Renting out, sharing economy, personalized economy or subscription economy is gaining rapid traction, especially in the developed countries. According to a study, 48% of participants prefer using subscription clothing where experts curate and deliver items based on previous purchases. Clearly, utilizing data for driving personalized recommendations is on the surge in the retail industry. The subscription-based retail businesses work on data-driven models to understand customer preferences and curate unique experiences for them. In fact, data-powered retail has resulted in a replenishment economy where products are intelligently shipped to the customer right before they are replenished, studying vast amounts of data from previous purchase cycles.
The educational reward and ranking system have been conventionally limited to the exam performance, assignments, and projects. But over the course of spending years in schools, students exhibit several qualities that are not accurately demonstrated or judged in traditional exam systems. By making use of big data, student achievements (academic or otherwise) can be mapped throughout to create a more holistic and diverse student portfolio. It also helps educators to determine the hurdles in understanding, challenges in learning, and other behavioral traits in students. Big data can be used to reduce student dropouts through prediction analysis. Teachers can study patterns of previous dropouts and provide assistance before it’s too late. Data-driven educational models can be incremental in offering customized programs to improve learning.
Data-driven businesses and process optimization is a change the world appreciates. But without identifying the right tech, creating a data-driven mindset, overcoming silo thinking, and addressing privacy concerns, the journey can be futile.
Approaching with an agile mindset with modern tech and compliance can help data-powered business models to thrive.