Data triggered growth

According to Crunchbase, the global venture funding in the last decade has significantly increased. Traditional VCs look for ROI through exits or IPOs. Smart VCs are looking at enhancing the value proposition of the startups by adding additional features to the primary solution provided and also by adding solutions at the adjacencies. In both cases, VCs are using data.?

Data collection, data aggregation, and data analytics are essential steps for enterprises to find growth opportunities. If you are an enterprise that is working on implementing new ideas, you want to collect data to monitor. You collect the right metrics to track the KPIs and objectives. Also, now that you collect the data, you may as well use it to find new ideas. The purpose of this thesis is to make a case of how to collect data and how to use it to enhance the value proposition. At the same time, this thesis aims to balance strategic and tactical ideas.

Availability of data has given ammunition to humans to spur their growth. In recent years, digital healthcare records have been instrumental in helping hospital administrators, doctors, and insurance companies to develop systems to predict human ailments and prevent them.?

Data about social media use and screen times has triggered discussions among mental healthcare providers, insurance companies, and policymakers to suggest creative ideas on how to mitigate the potential fallout. In the supply chain world, greater availability of supply chain details has helped transportation, insurance, and governments to innovate on the predictability of inventory expectations, potential supply shocks, and impact on prices.???

The travel and hospitality industry is another one that is going through tremendous growth due to the availability of travel, hospitality, and traveler preference data. There are new websites that offer price comparisons and send the best price alerts, suggest vacation destinations to tourists who are not able to decide and help airlines manage their supply (vs. demand).??

Personalized entertainment has gained traction after better availability of data about the consumption of content on streaming videos, movies, and social media sites. New movie sites, smarter apps to listen to songs, and a better selection of the right content for the right user on social media have sprung up in the last few decades.?

While the good guys flourished, the bad guys did too. Growth based on data did not just trigger the betterment of consumers but also played into the hands of the bad elements. The topics of Fake News, Phishing Fraud, and Hacking of sites with personal data have all seen creative (mis-)use of the available data.

Let's talk first about Data.

IDC predicts that by 2025, the world has to store 275 Zettabytes of data. The other day Newyork Times screamed “....data breaches happen all the time. Why don't you do something” in their famous article about data breaches. This and similar data-oriented reports triggered an avalanche of start-ups and products on data collection, curation, protection. In addition to data management, enterprises are also looking at new ideas that could detect newer revenue streams.?

Here is an attempt to look at the enterprises that grew newer markets and newer revenue sources by looking purely at the data that is already available. The focus here is on innovation that enterprises could derive by assimilating the data (internal and external) that is available.?

Enterprises that are about to begin their big data journey would start dumping all the data into a single lake first and then migrate the processed data into a data warehouse.

Why do you need a data aggregation platform?

Enterprises produce data all the time. Data needs to be collected and harvested. The latest digital evolution is helping industries to extract wisdom from data and adopt better policies as a result. Such wisdom helps Amazon to stock up products, Apple to sell more songs, Alibaba to achieve higher sales on Singles Day, venture capitalists to identify common problems and unique solutions for their start-ups. The following are quick strategic questions to be addressed to create a data aggregation platform.??

• How to create a data aggregation platform
• How to identify the right data?
• How to clean data
• Creating a datastore/feature store
• Data collection/update process (how frequently, who are the owners of the data, how to approve access to new API to access the data)

Side note: Here is a quick side note to the uninitiated about data storage. Three different terms are often used while discussing large collections of data, databases, data warehouses, and data lakes. The term database is used to refer to the collection of data that is available and used by individual users, typically in their server that stores highly-structured data. An example is data stored on a laptop or a mobile phone. Any data, say your email, photos, or text could be quite easily accessed by the user.?

Data warehouses are large collections of data typically used by enterprises where semi-structured or structured data is stored for access by multiple users for different use cases. The common use cases for data warehouses are for running analytics and machine learning programs.?

Data lakes are an even larger collection of raw data that is highly unstructured where enterprises collect and dump different types of data in a single location. Examples include all types of PDFs, emails, employee online activity info, multiple versions of software, etc. Data Lakes are quite cheap (compared to databases and data warehouses). They are predominantly used for fundamental research and complex AI research.

End side note.

The innovation process is quicker when the data exists in data warehouses. The semi-structured and structured data is available for developers to run analytics and build machine learning models to solve business challenges.

In our opinion, the first step in innovation is to promote data from data lakes to data warehouses to create feature stores. A feature store is a collection of structured data with the following characteristics: precise definition, high quality, accuracy, and temporal.?

Though enterprises could use Cloud storage services like Azure, Google Cloud storage, early versions of Hadoop, or even S3 as Data Lakes to collect data, eventually such data needs to be moved to data warehouses like Snowflake, Redshift, DynamoDB, DataBricks, etc. for ready access and to run machine learning use cases.

Now let's talk about growth.?

Growth comes from innovation and many innovation models exist. The most common one (shown below) compares Tech vs Market types to identify four types of innovations. (Side note: if you are curious about other innovation models, check here for ten types of innovations, and also here, here, and here for additional reading material).?

Is innovation slowing? According to research, based on the study of patents filed over time, the number of patents filed is slowing. But the more recent innovations like the internet, mobile phone, space research, etc. have greatly impacted poverty, sanitation, health, communication, climate, animal life, transport, and quality of life.??

The modern business world is full of innovations and optimizations triggered by data analytics. Yet, data-triggered innovations and optimizations have not attracted the same attention as creative-genius-triggered or accident-triggered innovation. There is a difference between optimization and innovation. Both of them result in new customers and new revenue streams. But true innovations create the possibility of solving a new customer challenge or solving an old one in a new way. Optimization generally improves an existing solution to perform better.

Data-driven innovations are not born from an individual’s ingenuity (Alexander Graham Bell’s telephone) nor are they born from the minds of visionaries (Henry Ford of the cars vs. horses fame). They do not come from the cross-pollination of ideas based on multiple varied applications (e.g. an idea to prevent blood from flowing in the opposite direction borrowed from nozzles of water bottles that bicyclists carry). But they have managed to make a sizable impact in many fields.?

Here are some ideas that were born purely based on data analytics. Quickbooks was introduced when Intuit saw that many users of their finance app Quicken were using it at their workplace too. Initially, the company misunderstood the data and felt that users were wasting their company time but later realized that these users were using the personal finance tool for corporate bookkeeping too. QuickBooks took birth based on such data analytics.?

The invention of the Gatorade drink is another example of data-triggered innovation. The football team coach of the University of Florida did not believe in the age-old practice of not letting players drink water before the games. People thought that drinking water will slow them. But the coach realized that the players were losing a lot of water through sweat and they need to stay hydrated. They studied the sweat to understand what minerals and salts the players are losing. They created a drink that replenished the minerals and salts to help the players play a better game. Check here for some more data triggered innovations in football games?

When analytics found that men buying baby diapers also are prone to buy beers (and hence suggested retailers place the two products closer to each other) is more an optimization triggered solution. Similarly, when Walmart stocks more strawberry pop tarts when a hurricane is announced, or when Facebook found a correlation between smart people and curly fries (apparently among those who like curly fries, college-educated rank higher), the solutions that may result are because of optimization.

Irrespective of the approach (optimization or innovation), enterprises need to process data (both internal and external) for newer revenue sources or expand their customer base. History is replete with examples of organizations that failed miserably when they refused to see or understand the data available in plain sight. Kodak and Blockbuster missed the writing on the digital wall (though Kodak indeed invested in Digital Cameras and also in online photo-sharing app), automotive manufacturers missed the invasion of battery-powered cars until Tesla released theirs, and telecom manufacturers missed the power of mobile devices until Apple revolutionized the smartphone industry with touch screen and apps.?

Innovation can also happen when two simple benefits are merged to provide a greater benefit and in the process create a new and stronger revenue stream. Let's discuss a couple of examples. Vehicle drivers currently use Map apps to pick the best route. Map service providers could use the same data (map data, traffic data, app usage data, weather data, etc.) to detect roads in need of maintenance. Also, Maps could predict traffic locations that need a certain number of emergency vehicles due to more frequent accidents.?

Digital money transfer systems are another example. It started with the peer-to-peer transfer of money (one of the pioneers being Paypal in the USA). Later digital money transfer systems, that proliferated across countries and continents, also used different mediums of transfer such as messages, telephone numbers, and email. Digital money transfer also expanded into currency conversion and, of late, to facilitate crypto transfer and payments.?

Phew!!! At last, now let's talk about data-triggered growth.

Scientists and researchers have tried to develop a simple theory to help in growth and innovation. But they have failed. The best way to grow is to study other growth ideas. And the best way to data-triggered-growth is to study other data-triggered-growth ideas.??

Here are some growth ideas that were developed based purely on the availability and the study of data rather than a stroke of genius or by accident. Side Note: Each of the following growth ideas is discussed very briefly to quickly get to the gist of the idea. In some cases, to achieve brevity, we sacrificed language.?

1. Anonymized usage of cell phones to optimize traffic conditions and traffic routing. The same could be used for road maintenance. This further helps in quicker safety response to drivers struck in accidents.??
2. Easy mixing of weather and pesticide data to use for crop yield prediction and help with the operations of, say, grain wholesalers, vineyards, livestock suppliers, insurance companies, etc.
3. Employers to offer newer Healthcare options to employees by predicting employee health
4. Use social media and gaming knowledge to create new ways of engaging and teaching students. Education experts are suggesting merging social media with education.?
5. Monitor air quality based on weather, traffic, and others to alert individuals.?
6. Help SME retailers reach out to consumers using an aggregator platform; connect retailers with wholesalers. In other words, integrating the value chain connecting Manufacturer - Distributor - Wholesaler - Retailer - and Consumer.
7. Create a marketplace for suppliers and buyers of used, limited-edition, antique, or high-value goods normally not found elsewhere.
8. Create restaurants, retreats, and recreation centers to provide personalized and unique experiences to customers who can afford them.
9. Develop SaaS platforms for Accounting (manage books, integrate with supply chain and operations, compliance, report generation), Marketing (digital ads, tracking customer preferences, trends), or HR organizations (manage Leave of absence, disability management, etc.) to provide best in class solutions and create dashboards based on cross-business anonymized data.
10. Integrate digital payments solutions with operations (say retail or transport) that will create better access to customers; similar to buy-now and pay-later; Point-of-sale lending.
11. Quick and easy delivery of food, laundry, essential items, medicines, home building supplies, in a very short time (say one day or even two hrs) based on demand, availability, and distance; This helps the supply chain players manage supply (vs demand); personalized services based on cold start and priors;??
12. Underwrite commercial carriers (trucks, ships, buses) which were not supported by traditional insurance and underwriters
13. Convert a credit card problem into a loan problem to help workers with seasonal and variable incomes?
14. Lending to the underbanked. Asset-based non-traditional lending. Managing lending risk using non-traditional features. Custom lending programs for blue-collar workers and SMEs. P2P lending.?
15. Help video game players form teams and compete in competitions. Help advertise and connect with the right audience. Help game creators to upload games and earn.?
16. Help form communities of music lovers, adventure sports enthusiasts, meditation lovers, pregnant women, runners, hikers, ham radio operators, truckers, antique collectors, beauticians, bodybuilders, backpackers, stock traders, beer lovers, climatologists, based on data from social media and online activities
17. Provide high schoolers access to relevant online class material and personalized content based on their choices, grades, plans, etc. Also provide online content for teachers and administrators based on news, student stated or unstated opinions, and government policies
18. Aggregate online content for students seeking specialized knowledge in tech, fixing home appliances, home projects?
19. Rental management of automotive (cars, boards, airplanes, RVs, etc.), homes (apartments, rooms, couches, etc.), runways (rent-a-runway), earthmovers, gardening equipment
20. Competition management: Help students and teachers participate / create / administer / track / report quizzes and competitions?
21. Rental property management platform: Enable renters by quickly and safely approving tenant applications for rentals. Loyalty program for tenants even when they move to new cities. Manage renter risk management for landlords
22. “Own your healthcare records”: Help patients take their records with them, allow approved third parties to create dashboards. Help insurance companies focus on preventive management?
23. Compliance and Regulation management: RegTech and SupTech are newer areas of tech innovation where data collation at the enterprise level to create reports and dashboards to comply with national and multi-geography regulations
24. Upgrade and Convert apartments & houses to host travelers
25. Dating & Linking services: Help link like-minded people, sportspersons, outdoor enthusiasts
26. Cyber fraud: Authentication. Preventive predictions
27. Interaction management among consumers, brands, manufacturers, influencers,?
28. Carpooling or vehicle-pooling for long-distance travel. Vacation-pooling.?
29. Finding (and making appointments) with doctors, mechanics, tutors, handypersons, painters, portrait makers, plumbers, security guards, bodyguards, nannies, baby sitters.
30. Contract management: Track expediting contractors. Link actionable clauses with enterprise dashboards and take actions. Track KPI against contract clauses; manage changes to contracts.
31. Homeownership: Connect sellers, buyers with mortgage lenders, realtors, and home builders. Track property tax and integrate it with lending solutions.
32. Platform to provide feedback for consumers about products and services. Expand to doctors, restaurants, taxi services, grocery shops, laundry services, etc.
33. “What happens to your digital assets after you die”: Platform that collects all of your digital assets including your pictures, documents, online access to your accounts, access to your bank, passwords to the security system/home security cameras/wifi, etc., and passes onto to the authorized family members
34. Marketplace and platform for the following activities
35. Cooking: cooking recipes, vegetable vendors, cooking utensils, chefs, ads, feedback, and ratings
36. Pets: dog walkers, veterinarians, advice, sharing of pictures, selling/buying, pet food,?
37. Cars: connect buyers, dealers, used cars, rating agencies, repair mechanics, spare parts, service station, insurance, car registration, car transport, lending
38. Flowers: delivery, cut-to-order packaging, wholesale sourcing,?

Let’s look at some practical examples. Below are a few startups that worked on ideas that are similar to the one described above.???

• Shopify converted small retailers PoS terminals into online sales terminals and other tools to launch their online operations and kept them in business when the pandemic struck
• Substack is a media innovation to help writers create their own business, publish content, and also manage their revenue. It also helps writers build up their readers and audiences. Also offers a mentorship program to budding writers?
• Hinge, the recent dating app that is helping find partners online, found that its video-chat option and virtual dating option attracted a lot more attention than anticipated. And hence it was made the main feature of the app.?
• Etsy provides a marketplace for crafters, artists, and collectors to sell their handmade creations, vintage goods (at least 20 years old), and both handmade and non-handmade crafting supplies.

Conclusion: Data is the backbone for growth. Enterprises that wish to expand market and revenue should use data-triggered growth. Such data-triggered growth would have a wider impact on customer experience. We strongly believe that enterprises can kick start growth with data identification and data aggregation. Later they need to study the data to identify (i) a better solution (ii) a new idea, and (iii) an adjacency.?

Credits: This paper would not have been possible without the conversations and contributions of Puneet, Gail, Vikrant, Arathi, Sridhar, Farideh, Hamzah, Lalatendu, Kishore, Sumanta, Pankaj, Adheesh, and Vivek.