Closing the gap between “Big Data" and "Big Business"
How to Close this Gap with Innovation in Business Models

Big Data is an area of digital transformation that refers to handling information that, owing to its volume, variety and need for rapid analysis, cannot be processed or analyzed with traditional tools, posing a challenge in technology, security, confidence, veracity, culture and special skills. 

Big Data, as a technological megatrend creates opportunities for emerging markets, such as Mexico and Latin America to develop start-ups that will serve to solve multiple challenges. Startups make use of digital technologies and have a high potential for escalation. Talent, data and knowledge comprise the channel for closing the gap between Big Data and big business.

The new data-based business models for start-ups offer an interesting taxonomy:

  1. Free data collection and aggregation. The companies in this group create value by collecting and aggregating data from a large number of, mostly free, available data sources (social networks or crowdsourcing), although paid data are also included. Subsequently, the other key activity is data distribution through an API (application programming interface) or web control board. 

    Its income models are usually advertising, commissions for intermediation, subscriptions or commissions for use. 

  2. Analytics as a service. The companies in this group are characterized for conducting analytics with descriptive, predictive and prescriptive techniques on the basis of data provided by their customers. The analyses are distributing by means of an API and by visualization. Offerings vary from fraud detection, improving marketing activities, customer service and attention to increasing sales.   

    The companies in this group focus on businesses that offer customized solutions. Their income model is predominantly based on subscriptions or commissions for use.

  3. Generation of data and analysis. These companies share the same characteristics, their central activity is the generation and analysis of their own data based on crowdsourcing, web analytics, smartphone data and physical sensors.

    B2C and B2B business models can form part of this group. Some companies sell physical devices to capture data and others generate income by selling analytics. 

  4. Knowledge discovery based on free data. This type of companies normally use data that is freely available or resulting from their own analytics.

    These companies’ offerings vary, from (1) automatic monitoring of hotel website reviews; (2) hotel recommendations based on booking sites; (3) identification of relevant social media "influencers"; (4) identification of emerging trends based on real-time data flows, such as Twitter or Facebook; and (5) identification and interaction with potential clients on social media platforms. 

    These companies provide a variety of income models, such as subscriptions, commissions for use, advertising or intermediation commissions. 

  5. Data collage from multiple sources and analyses. Companies from this group aggregate own data provided by their customers, together with others free sources to enrich them, and analyze these data to generate a benchmark. Some examples are: (1) monitoring and analysis of digital web marketing to assure the success of financial campaigns; (2) monitoring commercial management climates and prices; monitoring social networks (YouTube or Facebook), counting visits for entertainment companies. 

The majority of its business models are B2B and its income models are based on subscriptions.
In Mexico and Latin America in general, data collection by companies has not been an end in itself, but a byproduct instead. Therefore, the key does not lie in the volume and variety of data handled by companies, but in the speed with which they are used and improving customer-oriented value offerings. 

*By Martha Corrales, Innovation and Entrepreneurship professor at EGADE Business School.