Today, data doesn’t just drive businesses—it defines them. Data has become a key input for driving growth, enabling companies to differentiate and maintain a competitive edge. As Deloitte’s Data Valuation Report puts it, “the effective use of data can allow businesses to separate themselves from the pack, gaining first-mover advantage to become leaders and disruptors in various ecosystems.”
Businesses that rely on data management tools to make decisions are 58% more likely to beat their revenue goals than non-data driven companies, based on responses from a Forrester survey published on CIO Dive. In addition, data-savvy businesses are 162% more likely to have significantly surpassed their revenue goals when compared to their counterparts.
Yet, for something many executives consider one of their most significant assets, few business leaders can articulate what their company's data is worth. According to Forbes, one reason could be because most CIOs and CFOs value their company’s data based on basic math.
But using traditional accounting frameworks to define the value of data is problematic. Today, financial analysts, investors, and board members expect data-driven startups and businesses to determine the value of data assets based on the extent to which they could be used to advance key initiatives that support an organization’s overall business strategy.
Going forward, the most successful companies will be those who understand the value of their data and how to protect it.
Capitalizing on insights derived from data, employees can make better decisions, evaluate risk, and find ways to engage and keep customers. Here’s why companies should know what their data is worth.
1. Direct Monetization
McKinsey’s 2018 study found that across industries, the primary objective of data is to generate new revenue. Thus, direct data monetization is often one of the first methods considered to capitalize on the value of company data.
Direct data monetization involves selling direct access to your data to third parties. You can sell it in raw form or in a form that’s already transformed into analysis and insights. Typical examples include contact lists of potential business prospects or findings that impact buyers’ industries and businesses.
2. Internal Decision Making
Understanding how to leverage data to drive business value can help you understand where you should be minimizing costs, as well as where you should be investing to realize potential ROI.
For example, imagine you’re planning a go-to-market strategy for a new product. Instead of starting from scratch and hoping a new strategy works, analyze the data previous product feature launches. Replicate what worked and don’t implement anything that didn’t.
Still, this is easier said than done. While 91% of companies say that data-driven decision-making is important to the growth of their business, only 57% of companies base their business decisions on their data.
3. Mergers & Acquisitions
Every merger and acquisition decision is driven, at least in part, by data. With access to the right data, you find out what’s going on within the company you’re planning to acquire or merge with. Proper valuation of a company's data can bolster these merger and acquisition chances, while an inaccurate valuation of data assets can be costly to shareholders during these deals.
As this Forbes article points out, “Microsoft’s $26 billion acquisition of LinkedIn wasn’t for its 1990’s-style web app or the hardware that hosts it.” A significant reason was the value of LinkedIn’s data about professionals and companies. One could say the same for other notable acquisitions like Facebook & WhatsApp, and Salesforce & Tableau, to name a few.
Now that you know why valuing your data is essential, how exactly do you do it? The answer isn’t cut and dry. No single equation can assess the value of a company's data with 100% accuracy. The data’s value depends on several factors, including usability, accessibility, and cleanliness. That being said, there are several different ways of getting a fairly accurate valuation. Let’s take a look at some of the most common methods.
When considering the value of data, your first thought might be, how much could I get if I sell it? In most cases, this involves the sale of data sets or access to business data as a service. For example, credit reporting companies aggregate payment track records and sell credit history information to institutions looking to support financial decisions.
When using this method to value your data, it’s crucial to consider that different business models, audiences, and data volume can often complicate the real-world value of data. You also need to make sure you have permission to sell the data that you own. Under GDPR, CCPA, and other consumer privacy regulations, there are restrictions on how you can use certain customer data.
You don’t have to monetize your data directly—you could also leverage it to automate time-intensive processes that incur human costs. Increasingly, companies automate repeatable tasks using chatbots and AI. For example, companies can use cloud-based accounting platforms with a broad range of third-party applications that autonomously collect and organize financial data to minimize the time spent on manual data entry.
By incorporating automated solutions that leverage existing data, businesses can allow employees to focus on other high-value tasks.
This valuation method occurs when an organization combines a set of data with other information to create new value. For instance, an enterprise can aggregate a batch of company emails and extract data, such as destination, sender, subject, and time stamps. Then, it may uncover a strong correlation between employee performance and specific email patterns.
Companies can clarify the benefits of this type of valuation method by performing an A/B test, assessing the value of new business practices introduced before and after incorporating external data.
Many companies use recommendation engines to drive value. For example, Netflix increases its revenue and stickiness by matching content with customers’ tastes and viewing habits. Similarly, Amazon recommends products, including those that others have also viewed or purchased. In doing so, they’re able to increase orders through cross-selling and up-selling.
Risk of Loss Value
This final method of valuing your data is relatively straightforward: If you were to lose access to your data, how much would it cost your business? The most recent IBM/Ponemon Institute study calculated the cost of a data breach at $242 per stolen record, and more than $8 million for an average violation in the US.
And while malicious incidents, like data breaches, often appear in the news, they’re actually a less common form of cloud data loss at most organizations. According to our latest Salesforce Data Protection survey, human error is the most common cause of data loss, making up almost half of all incidents. More often than not, this is the result of having too many people with administrator permissions, which can lead to data loss or corruption that may go unnoticed for days or weeks.
Data downtime could have significant costs, depending on the amount of time it takes to recover and other critical factors. During the recovery process, your company could experience increased labor costs, productivity losses, non-compliance fines, and a hit to your reputation.
For example, suppose a Salesforce administrator is spending days or weeks trying to assess the scope of a data loss and how to recover. In that case, that's time they aren't spending on high-value projects to the organization. Or, if you can’t pull up an opportunity in Salesforce or are missing a critical piece of information, you risk impacting things like sales, orders, and deliveries, grinding business to a halt.
Like many Salesforce stakeholders, you might assume that your data is protected because it’s in the cloud. The truth is, though, most cloud platforms like Salesforce require shared responsibility for keeping data safe. These platforms provide reliability and security controls, but customers are ultimately responsible for the errors and corruption they create. Salesforce themselves recommend a third-party cloud data protection solution and emphasized this further when they retired their last resort Data Recovery service on July 31, 2020.
For more on this topic, watch the recording of our virtual event titled, "Understanding What Your Salesforce Data is Worth...And How To Protect It", where best-selling "Infonomics" author and recognized authority on data strategy Doug Laney shared his best practices for managing, monetizing, and measuring your enterprise data.