Use data to disrupt business

Data can be used to disrupt business in a number of ways, including:

• Creating new products and services: Data can be used to identify new customer needs and to develop new products and services to meet those needs. For example, Netflix uses data to recommend movies and TV shows to its users. Airbnb uses data to recommend listings to its guests.

• Improving existing products and services: Data can be used to improve existing products and services by identifying areas where they can be improved. For example, Amazon uses data to improve its product recommendations and to reduce the number of items that are returned.

• Making better business decisions: Data can be used to make better business decisions by providing insights into customer behavior, market trends, and operational performance. For example, Walmart uses data to optimize its supply chain and to reduce inventory costs.

• Disrupting existing industries: Data can be used to disrupt existing industries by creating new business models and by offering new products and services. For example, Uber and Airbnb have disrupted the transportation and hospitality industries, respectively.

Leveraging data to disrupt businesses is a concept often associated with data-driven innovation and digital transformation. Here are some ways data can be used to disrupt business models, along with references where applicable:

Personalization:

Tailoring products and services to individual customer preferences can be a powerful disruptor. Netflix, for example, uses data to recommend content to users based on their viewing history.

Reference: "How Netflix uses big data to drive success"

Marketplace Platforms:

Platforms like Airbnb and Uber have disrupted traditional hospitality and transportation industries by connecting providers and consumers through data-driven platforms.

Reference: "How Airbnb and Uber Used Digital Platforms to Disrupt Incumbent Industries"

Predictive Analytics:

Companies are using predictive analytics to optimize supply chains, reduce downtime, and improve decision-making. For example, predictive maintenance in manufacturing reduces equipment failure.

Reference: "Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die" by Eric Siegel - Book Link

Subscription Models:

Transitioning from traditional sales models to subscription-based services can disrupt industries. Adobe's move to a subscription-based model for its software products is an example.

Reference: "Adobe Creative Cloud is a massive success, but you wouldn't know it from the company's financials"

Data Monetization:

Companies like Google and Facebook have built business models around user data, using it to target advertising and generate significant revenue.

Reference: "How Facebook Makes Money: Advertising"

AI and Machine Learning:

Implementing AI and machine learning in various industries can lead to disruptive innovations. Self-driving cars, for instance, have the potential to disrupt the transportation industry.

Reference: "Self-Driving Cars: The Future is Here"

Healthcare Analytics:

Advanced analytics in healthcare can lead to improved patient outcomes and reduced costs, disrupting traditional healthcare models.

Reference: "How Big Data Is Disrupting the Healthcare Industry"

Retail Data Analytics:

Retailers use data to optimize inventory, improve the in-store experience, and personalize marketing. Amazon Go's cashier-less stores are a disruptive example.

Reference: "Amazon Go: A case study in disruption"

Some examples of how companies have leveraged data to disrupt businesses and industries:

Retail & Commerce:

• Amazon uses customer data and analytics to recommend products, tailor promotions, and optimize supply chain - key to their massive disruption of retail.

• This allowed Netflix to offer a wider selection of content and to provide a better user experience.

• Google used data to disrupt the advertising industry. Google uses data to target ads to users based on their interests and to measure the effectiveness of ad campaigns. This has made Google one of the most successful advertising companies in the world.

Media & Entertainment:

• Netflix used data to create a new business model for streaming video. Instead of relying on advertising revenue, Netflix charges its users a subscription fee. Netflix analyzes audience data to create and promote new original content as well as customize recommendations. This fueled their rise as a dominant force in media.

Transportation:

• Uber's use of maps data, traffic data, and rider data has disrupted the taxi and transportation sector via ride-sharing.

Finance:

• Companies like Mint and Credit Karma have used open banking data, financial data analytics and personalization to disrupt traditional financial services.

Healthcare:

• Startups like Oscar Health analyze patient data, costs, and outcomes to disrupt insurance markets with new models aligned with digital lifestyles.

The common theme is leveraging data to understand users, personalize offerings, optimize operations, and build competitive advantage. Data is a key enabler for disruption across sectors.

Sash Barige

Feb/22/2018

Photos: unsplash.com

Here are some referenced sources for the above information:

• McKinsey article: "The data-driven business revolution"

• Harvard Business Review article: "Competing on analytics"

• Forbes article: "How data is disrupting every industry"

• Deloitte article: "The future of business is data-driven"

• https://hbr.org/2014/10/how-uber-and-airbnb-could-disrupt-industries

• https://sloanreview.mit.edu/article/can-netflix-disrupt-the-tv-industry-a-case-study

• https://www.cbinsights.com/research/industries-disrupted-amazon/