Big Data in Business: Data, Revenue Streams, and Valuations
What’s this about: Companies are sitting on a goldmine of data that is becoming increasingly valuable for their growth. The value of information is at an all time high, and the transformation into a data-driven business can greatly improve revenue streams and valuations. A data-driven business is one that transitions from experienced-based, leader-driven decision making to data-driven decision making.
>>> Before reading this piece, make sure to check out “Big Data in Business: Data Requirements for AI-Driven Businesses.”
Impact of Big Data on Business Environment
Big data is completely flipping traditional business valuations upside down. While oil and energy companies once topped the list of most valuable firms in the world, it is now dominated by tech companies like Apple, Facebook, Amazon, and Microsoft. What do all of these companies have in common? Data, data, and more data.
After all, as Clive Humby put it back in 2006, “data is the new oil!”
This data revolution is dramatically impacting the way organizations are behaving in the new environment. For one, they are beginning to recognize the value of being a data-centric business. Data-driven firms often have significantly higher valuation multiples than non-data-driven firms, both within the same industry and outside. At the same time, they are receiving more requests from outside parties to buy and use their data.
Organizations are also looking for new revenue opportunities brought on by this data explosion, which is causing increasing pressure to diversify revenue streams and grow margins. Traditional methods involving customer acquisition and retention are becoming less common, and businesses are being presented with a brand new set of consistently improving technologies that are dropping in price. This may sound intimidating to leadership across sectors, but by embracing these changes rather than turning away from them, they will open up countless new doors, including new partnerships and revenue streams.
The gap between data-driven and non-data-driven organizations has never been greater. Companies with good data analytics capabilities are twice as likely to be in the top quartile of performance within their industries, and these big data players are feared among those who have yet to make the transition. [1]
Driving Business Value
Data analytics is a major driver of business value thanks to its potential to generate insights that lead to better business. Statistics are consistently showing that data provide a great opportunity for firms to increase revenue, lower operational expenses, and expand their customer base. For example, data-driven organizations are 23 times more likely to acquire customers than their peers, and increasing data usability by just 10% could increase revenue by over $2 billionfor the average Fortune 1000 company.
There are five attributes of data that dramatically impact key financial measures: quality, usability, intelligence, remote accessibility, and sales mobility. By improving on these attributes, even slightly, a data-driven business can see huge financial returns. [2]
Here are some of the main ways data can financially impact an organization:
Increase employee productivity: To increase the usability of data within an organization, they should be presented more concisely and consistently across platforms, which can dramatically increase the productivity of employees.
Return on Equity (ROE): ROE is used as an important indicator of how well a business is growing. By increasing the quality of data and access by sales people by 10% more than existing levels, the average Fortune 1000 company can increase ROE by 16%.
Return on Invested Capital (ROIC): ROIC measures a businesses’ efficiency of allocating capital to profitable investments. The average Fortune 1000 business can increase ROIC by 1.4% by increasing the mobility of its sales organization’s data by 10%.
Return on Assets (ROA): ROA indicates an organization’s ability to efficiently use its resources to drive income. By increasing the data attributes of intelligence and accessibility by 10%, the average Fortune 1000 company would see an increase of 0.7% in ROA.
Investments and Acquisitions Based on Data
Data is also playing a major role in the investment lifecycle of organizations, providing insights needed to deliver ROI and maximize returns. Prior to acquisition, investors forecast based on existing revenue and pipeline data. But now, companies are pulling valuable information from hundreds of different data sources. It is crucial to have these valuable data organized and continuously updated if you want to catch the attention of potential investors and partners.
Data analysis is a top priority in the investment and growth period, meaning it’s important to compile all data into a holistic view to discover the greatest opportunities for ROI. Analyzing a company’s data assets can reveal a lot of things, such as if sales are low on the most profitable products or services, or common demographics to build customer segments of who generates the most revenue. Data is crucial to forming the best strategy for growth and executing that strategy, and many of today’s investors will walk away if there is no data strategy in place.
We are seeing more and more instances of companies being bought and sold based on data alone. For example, IBM acquired The Weather Company in 2015 just to gain access to the latter’s weather-related data resources. Following this acquisition, IBM could sell the valuable data to other companies wanting to use it for understanding weather patterns. (This is what makes IBM one of the big players!)
To attract more interest for a company, leadership should have access to a wide-range of continuously updated data, such as:
Index of products and services: There should be a list of clearly defined products and services offered by the company, with all similar products and information systems classified with the same code or description. It should be easy to differentiate between products and services in this list, since groupings can make it difficult to analyze a product’s individual value.
Master repository of customers: Companies should possess a list of all customers with their details pulled together in one place so they can be identified with the same code or description across systems. The same is true for business names, which should be consistent.
Business costs: There should be a record of all business costs for products and services sold.
Company sales: It’s important to have access to all company-wide sales, which should be able to be broken down by product category, region, etc.
Identifying Valuable Data
The world produces around 2.5 quintillion bytes of data per day (that’s 2.5 with a whopping 18 zeros after!). Each one of these data hold their own value for businesses. And this is just the beginning, with most of this massive amount of data being produced in the last few years. It is crucial for an organization to understand the value of its data by identifying and classifying them.
By performing an inventory of data, a firm can not only assess the quality of them, but also identify any gaps that need to be filled by reaching out to third parties.
There are a few basic key features of valuable data assets:
The data must be identifiable and definable.
The data must have economic benefits, such as useful applications that can result in future cash flow.
The business must have full control over the data, meaning rights to utilize them according to laws and licensing arrangements.
Oftentimes, first-party data just isn’t enough, which is why many organizations seek out third-party data. This provides a way for businesses to monetize their own data even further by providing access to third parties, for example through an API, which creates shared functionalities and enables regulated data sharing. This is one of the many doors opened by transforming into a data-driven business. Not only does it bring in more revenue for a business, but selling business data also allows companies to form mutually beneficial relationships with other organizations. Starting to see a trend?
Here are some examples of leading big data companies that sell their data:
Oracle openly sells data to marketers all across the globe, with the Oracle Data Cloud providing business-to-business marketers with more than 400 million business profiles and thousands of audience segment profiles.
Acxion has “the most expansive and compliant data offering in the world,” which includes over 10,000 attributes covering more than 2.5 billion consumers.
PayPal possesses billions of personal and financial records that it regularly shares with third-party partners all across the globe, such as major banks like Wells Fargo and Bank of America.
Another important step to assess the value of data for stakeholders is to differentiate between data, content and information. You’ve undoubtedly heard the term “data” thrown around in many different contexts, but it consists of a few moving parts. Data are simple, raw, and unorganized facts that consist of basic subscriber information (BSI), transactional data and content data.
By combining BSI and transactional data, we end up with non-content data, which were traditionally believed to be lower in value when compared to content data. However, this has changed over the years, and non-content data are now accepted as a way to gain valuable insights.
When a company organizes all of these data, processes them, and provides context, they become information. This information is the most valuable of all for decision making, but each one of these data assets are crucial for increasing a company’s value. To bring all of the data assets together, organizations can use data correlation, which can involve connecting data in one silo to data in another to create more information in the process.
The Importance of Data Accessibility
Determining the value of data can be tricky since it can’t be measured by data volume, data speed, or data quality alone. The best way to increase the value of data is to make them accessible to those who need them, exactly when they need them.
All of those eighteen ZEROS in the 2.5 quintillion data are worth one big ZERO if an organization’s team can’t access the data. Every level of the business should have access to data to drive decision-making and critical insights. Whether it’s front-line staff, new interns, managers, or C-suite executives, each employee can leverage data to become more efficient and valuable.
To achieve excellent data accessibility, every user must be provided with the right tools, ideally those with a zero-learning curve that support a wide range of user types. Artificial intelligence is often relied on to achieve this accessibility, with AI solutions enabling users to use their own words to search for important data. Each user should also be enabled to build dashboards in seconds without having to learn the intricacies that would normally slow them down.
By achieving intuitive, self-serve data accessibility, businesses can leverage their data even further to get ahead in the data-driven business environment.
The Most Valuable Resource in the World
Data has replaced oil as the most valuable resource in the world. And unlike oil, which we have less of each year, the amount of data we have exponentially grows each year. In the past, business decisions were made based on experience and gut-level reaction because there were simply not enough data to drive decision-making. But with 2.5 quintillion bytes of data now being produced per day, there is no shortage.
These data are disrupting today’s businesses and their valuations, forcing any organization to become a data-driven business if it wants to increase its chances of success in this highly competitive time. Data are unleashing new revenue and financially impacting organizations by increasing employee productivity, return on equity, return on investment capital, and much more. These new opportunities come with great responsibility for any data-driven business, which must ensure that it’s aware of the legal and ethical implications.
>>> To learn more about the legal and ethical implications of big data and AI, check out my previous piece titled “AI & The Law.”
The investment lifecycle is also being impacted, with data now being the most important asset investors look at. But all of this means nothing if a business can’t transform into a data-driven organization, identify its valuable data, and make it accessible to as many employees as possible. With this approach, any data-driven business sets itself up to become a leader in this new environment.
>>> Make sure to look out for the next installment of this series coming soon!
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Notes
[1] https://www.pwc.co.uk/data-analytics/documents/putting-value-on-data.pdf