Will your company be valued by its price-to-data ratio?

The job of every security professional is to protect their organization’s price-to-data ratio. In the past, it was typically the Sales and Marketing teams in the hot seat driving a company’s valuation by maintaining sales goals to meet quarterly net income targets. But now, it may be just as important, or even more important, for the security team to protect and maintain the integrity of proprietary data to generate true, long-term enterprise value.

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Anyone who watches the stock market knows that typically investors track a company’s price-to-earnings ratio, which is the company’s value divided by its net income. Investors of various asset classes may also value companies based on sales, free cash flow or EBITDA (Earnings Before Interest Taxes Depreciation and Amortization) multiples. All of these methods consider the current financial snapshot of the company’s performance, and then, in theory, try to estimate a future risk-adjusted growth rate to create an accurate valuation. But would it make more sense to measure future value of certain companies by applying a price-to-data ratio?

AI changes everything

For many companies, their future product or service success will be tied to the performance of their AI algorithms. And these algorithms are only as good as the data – in particular, large quantities of proprietary data – that trains them. Thus, in theory, the companies with the greatest quantity of proprietary data should have the best performing businesses, to the extent that algorithms are core to the business success. This may make sense for companies like Google, Facebook and Amazon, whose user experience and business models are closely tied to machine intelligence and proprietary data. It may also make sense for big pharma companies, like Johnson and Johnson, Novartis or Celgene, who all rely on cutting-edge drug discovery techniques to maintain and grow their market-leading positions.  The list of industry verticals and companies is vast, if one considers how data and AI will influence the future of many, if not all, industries.

Data has always been important in business, of course. Business intelligence dates back to the late 1990s. Data was less important in the pre-digital age though. Marketing — both to consumers and to Wall Street — had outsized importance in creating brands and companies that became household names.

The big change to all of this is artificial intelligence. AI has the power to transform businesses by offering unprecedented personalization to consumers. Companies can also apply AI to business intelligence to unearth game-changing insights. We see this today as companies like Amazon and Netflix hold onto customers and entice new ones by making their offerings “sticky” by recommending shows, movies and (in Amazon’s case) products that customers are statistically likely to enjoy or need.

The catch is that AI is only as good as the data you put into it and you need a critical mass of data for it to work well. That’s good news for Amazon, Google, Microsoft, Netflix and Facebook, who have petabytes of proprietary data and mechanisms in place to continue to draw such data for years to come. Even Apple, the world’s first trillion-dollar company, could be ultimately be seen as more valuable for its stockpile of consumer data than the innovative hardware it creates.  

Below that top tier of companies, businesses across industry verticals will be valued for their data. For example, security companies will win if they have access to larger quantities of malware, threat intelligence, and corporate incident and event data to better train their defensive algorithms. Retailers will need data to recommend the right products to their consumers. Entertainment companies will need data to recommend new movies and TV shows and they’ll use data to determine which properties to develop. It’s hard to think of any company that will thrive in the next decade without access to large amounts of pristine data. That’s why data is so valuable right now.

One caveat: consumers are much more circumspect about the way businesses collect and use their data. GDPR in Europe and the California Data Privacy Act of 2018 both set strict standards on corporate data collection. But the top tech companies offer value in return for the data they collect. That’s why it’s a sustainable model for them.  Data privacy laws are more likely to hurt smaller companies that don’t have such relationships and rely on intermediaries for such data.

The potential of data reserves

One could look at data in the 21st century as the equivalent of owning proprietary underground oil reserves in the past century. As ExxonMobil and BP have been valued on their untapped reserves, companies like Facebook, Salesforce or Microsoft should be potentially valued on their data reserves – the data their have already collected, and perhaps not even leveraged, and the data that they will discover, collect and process in the future. Facebook or Salesforce may be obvious examples of consumer and enterprise data value, but think of the vast potential that is still to be tapped at Microsoft – they have corporate data, LinkedIn personal data and Xbox and Minecraft consumer data all within their proprietary control. This is extraordinarily powerful and puts the company in a tremendous position to create successful enterprise and consumer products and services based on the insight gained from this data.

Going back to Facebook, the company has taken some lumps lately, but at the time of this writing its market cap hovers around half a trillion dollars. That’s impressive if you consider that Facebook is a company that doesn’t really make anything other than provide high-quality processed data to advertisers. And this data is vast, proprietary and high-quality. It has excruciatingly personal information on approximately two billion people. You could argue that its half-trillion dollar market capitalization is based on the formula of Really Big Proprietary Data + Machine Learning Intelligence + Branding.

But recently Facebook’s value has suffered after high profile cases of data breaches, unauthorized access, data manipulation and inappropriate usage. Some would argue that the value has been reduced because of the brand tarnish, and a future prospect of lawsuits, regulation and user churn. But one could also argue that the biggest problem is that Facebook’s collection of proprietary data has been compromised and contaminated, and thus the value of the data has diminished, and the Price-to-Data ratio has come down.

Protect your organization’s price-to-data ratio

This value erosion can happen at any company or institution. Thus, it is the job of every security professional to protect their organization’s price-to-data ratio. In the past, it was typically the Sales and Marketing teams in the hot seat driving a company’s valuation by maintaining sales goals to meet quarterly net income targets. But now, it may be just as important, or even more important, for the security team to protect and maintain the integrity of proprietary data to generate true, long-term enterprise value. Of course, this will require the adoption of new processes and products, many of which will be dependent on well-trained artificial intelligence-based technologies. 

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