In today’s fast-moving world overflowing with data of every possible type and configuration, business leaders are struggling to maximize the value and utility of their data assets. Indeed, some report that more than 73% of corporate data assets go unused for analytics, while untold quantities are never monetized or utilized in any productive way at all. Yet in one study, more than 98% of company leaders aspire to a data-driven culture.
Data Value can be estimated first by creating a coherent inventory of data assets, and then understanding the relative merits of each asset with respect to six measures: Coverage; Recency; Depth; Uniqueness, Accuracy and Geography.
Data Utilization can take many forms, and the opportunities to extract every byte of value from data are myriad. They range from internal uses, such as those resulting from smart BI platform implementations; to customer facing data usage to support Customer Success initiatives; to externally facing uses that directly benefit sales, marketing, product launches and PR initiatives; to revenue creation initiatives wherein repackaging data assets to create incremental revenue streams. Creating incremental revenue from existing data assets can take more than a dozen forms, and is a worthwhile exercise to diversify revenue streams and grow both top and bottom line revenue.
After talking with hundreds of data suppliers and sellers, the team at Chrysalis developed an online, interactive scorecard tool to assist companies with valuing and assessing how well they’re utilizing their data assets. This free, private workspace gives users the opportunity to answer a few survey questions, and view a custom score of their current data utilization, and get a sense of the inherent value of their data assets.
It seems that everyone, everywhere is awash with data. Many of us feel we have more data than we can realistically manage and maintain, while still doing our day jobs.
Yet we also know that our data is tremendously valuable, and often experience this nagging feeling that we probably aren’t getting all the value and revenue from our data that we could. It’s not surprising, really. There’s a lot to know about using data to its full potential, and those dynamics are continuously and rapidly changing.
To help companies frame these important considerations, we built the Data Monetization Scorecard. One of our goals in creating this tool is to help companies differentiate activated data from what we think of as lazy data, and suggest a range of options for putting that underexploited data into action.
Activated data has been put to work, and is supporting operations, spotting trends, solving problems, delighting customers and bringing you business. Lazy data is lying around, taking up space on your hybrid cloud environment, brimming with unfulfilled potential, and not helping your business or your bottom line at all.
Based on our research, there is a lot of lazy data out there. In fact, according to a recent article by Inc Magazine, “About 73% of company data goes unused for analytics.”
New Vantage Partners recently conducted a survey of significant and Fortune 1000 executives, which found that:
- “Among 2018 survey participants, a nearly unanimous 98.6% of executives indicate that their firm aspires to a data-driven culture, up from 85.5% in the 2017 survey.”
- “Among these executives, 32.4% indicate that their firm has achieved this outcome, while the majority of respondents (67.6%) state that it is too early to determine if they will be successful in achieving this goal.”
A majority of the respondents were C-Suite executives, with most having the titles Chief Data Officer, Chief Analytics Officer and/or Chief Information Officer.
Our other goal is to give companies an empirical method of applying an objective value to their data assets. The scorecard takes the first step in that valuation, putting data asset value in context. For companies that want to do a more in depth calculation, we’ve also created the industry’s first and only Data Appraisal™ methodology and accompanying database of comparables for use in the calculations.
This approach, based on thousands of interviews with data collectors, suppliers, brokers, users, appraisers from other industries and deeply experienced strategists, supplies an empirical basis for data valuation, and a method to estimate potential revenue to be gleaned from specific data assets.
The system was designed to allow professionals to obtain a meaningful assessment of how well they’re leveraging and monetizing their data in about 5 minutes.
The scoring system itself is segregated into two main categories:
This section helps the user gauge how valuable their actual data is, specifically as it pertains to creating incremental revenue streams from it. By identifying each type of data and its characteristics, users get a customized Value score.
This section looks at how well the user’s data is being monetized and leveraged. Is it lying fallow or is it in use, benefitting the business?
Our valuation calculator starts with an inventory of data types. Users select the type(s) of data they possess, and input characteristics of each from a set of drop-down menus. The system is able to apply these values and render a Data Value expression.
Data Valuation Metrics in the calculator include:
- Data Type: what is the nature of your data? Is it permissible to remarket it, anonymized where necessary?
- Data Coverage: how broad is your data coverage for a given market? Does it cover enough that your data can be used for market-wide analysis?
- Data Recency: How fresh is your data? Do you get it daily, or hourly, or is it coming in monthly, or in batches? Data with great recency is always more valuable than older, staler data.
- Data Depth: is your data especially in-depth and jam packed with attributes, or do you have just a few data points?
- Uniqueness: how commonly available is your data? Even if you only have a few data points, having the right ones is what matters.
- Accuracy: is your data considered to be highly accurate and reliable? Is it validated to ensure accuracy?
- Geography: Does your data cover part or all of a country? Multiple countries? The world? These factors greatly influence the value of your data.
For users who would like to go further, and receive an in-depth Data Appraisal™, please contact us.
A company’s utilization scores pertain to how well the data is being used both inside and outside the enterprise. Data that increases efficiencies and smooths out work flows tends to bring internal value, whereas data that is leveraged for marketing, sales and to create incremental revenue streams is more outward facing.
The Business Intelligence market is replete with very sophisticated tools that deliver meaningful value and business results to users. Platforms like Sisense, Dundas, Yellowfin, Domo, Birst, Looker, Tableau, Infor, IBM, SAP, Oracle, Tibco and Qlik are just a few of the leading analytics and BI players worth considering.
Each of these systems offers corporate users the ability to look deeply into their own operational metrics and efficiencies, and gauge and visualize critical performance factors like repeat purchase rates, long term customer value, churn and marketing response rates, via real-time dashboards. Yes, they can be expensive, and yes, you need talented professionals to engage with these systems to get full value from them, but we all know they’re worth every penny.
A recent study from Dresner Advisory Services confirms that companies of under 100 employees have adopted BI technology more readily than bigger players, in an effort to level the playing field using this powerful asset, as opposed to hiring armies of workers.
Tracking and reporting on customer success is an important outgrowth of the typically more internally focused BI industry. Companies are increasingly pulling together explicit Customer Success Teams, whose role is to focus on the outcomes they can help their clients achieve. Different than customer service or account management, customer success is a separate and growing operational focus area. Yet according to Forrester research, “only 37% of leaders have a dedicated budget for customer experience improvement initiatives.”
Another data opportunity is for companies to take the extra step to productize their Customer Success analyses and deliver it to their customers. Too often these well considered insights are limited to internal sales and account staff. Instead, smart companies are now starting to take those sophisticated analyses directly to their clients, producing customized, specific reporting on their clients’ success.
What customer doesn’t want regular, data-driven reports on the value they’re getting from their vendors and partners? What account manager wouldn’t want to bring their customers meaningful insights into the performance and benchmarks they’re delivering?
Most companies get the need for this but worry about the cost. And while it’s true that it takes skilled, dedicated personnel to build and continuously deliver this kind of customer success reporting, the benefits do outweigh the costs, and there are good ways to substantially mitigate and efficiently control these costs.
A company’s own data is often an unexploited treasure trove of statistics, metrics and indicators that shine an impressive light on their capabilities and market leadership, when used correctly.
A recent B2B survey from Forrester Consulting shows that “organizations with data activation maturity were more likely to report increases across marketing/sales and customer metrics, with 73 percent reporting more rapid sales cycles, 73 percent reporting a higher marketing ROI and 77 percent reporting increased customer retention.”
We already know that these data form the basis for powerful case studies, but that’s only the beginning. The savviest marketers take a high level, aggregated view of their own data, and create entirely new, market-relevant insights that establish them as serious, industry authorities.
But they also combine that data with storytelling. Charts and graphs are powerful, but as the hugely influential Jay Baer, of Convince and Convert says, “don’t compromise the art of storytelling just to showcase data.” In other words, no, your BI platform can’t do all this for you.
The most impressive outcomes we see consist of:
- PR Alerts: Stats and metrics prepared specifically for trade press. The best programs are actually customized and written to speak to specific writers whose attention you want to attract by covering the topics they’re most focused on covering. An impactful PR strategy helps smaller or newer companies and challenger brands to level the playing field by getting far more coverage than they otherwise might. Writers and editors are always hungry for interesting, credible and relevant data points – so use your own internal data and analysis to give it them.
- Marketing Support: using hard data to create analysis-supported market perspectives, product benefits and customer outcomes adds credibility and impact. Intelligently pulled from a company’s own data, these power up marketing content, competitive positioning, new product launches and strategic initiatives like M&A activity.
- Analytical Thought Leadership Content: Thoughtfully reviewing and writing cogent analysis about a company’s own data is the best possible foundation for creating polished and serious blog posts, articles in trade publications, Linkedin posts, bylines and speaker content for conferences.
- Sales Support: Creating valuable content that sales people can use to generate intrigue, get meetings, move prospects along the consideration path and bring deals across the finish line will be warmly welcomed by a hard working sales team. But graphs and charts alone won’t work nearly as well as having thoughtful, written analysis and a compelling narrative around the data being displayed.
There are a number of approaches to creating these high impact materials. Some in-source with internal talent, while others outsource to specialty firms, but in every case the specialists needed include smart analysts, talented writers and editors, skilled data visualizers and experienced creatives and designers to pull all the pieces together and create these powerful sales, marketing and PR tools.
Companies rarely have the time or the knowledge to fully exploit every possible source of incremental revenue from their data. Even companies that are primarily data sellers know that there’s more they could be doing to monetize those data assets, but can’t always devote the time and resources to identifying it, testing it, and then rolling it out.
Our research shows that the highest scoring data utilizers make this activity a priority. And it makes intuitive sense: ignoring this incremental revenue is like being a retailer but only selling a portion of your inventory, or like having 6 legitimate buyer categories but only selling to 4 of them.
Companies should consider the set of options below, and ask themselves if they could be adding new revenue streams and reaching new customer groups by using their data in these ways:
- Swaps, Exchanges, Co-Ops and Mashups: sometimes 2 or more companies can come together to produce a wildly valuable data asset by combining components that each of them possesses. It’s a strategic consideration that requires some research and careful deal making, but it’s worth the time.
- Enhancements and Enrichment: Data owners can enhance their data by buying or licensing other data to enrich it, so as to suit a specific or a new buying audience.
- New Data Products: by aggregating and in some cases anonymizing their own data, companies can create highly valuable data products that get sold as finished reports, branded indexes or online subscriptions. Synthesized with intelligent analysis and thoughtfully written content to put the data in context, data being sold in one format can be brilliantly re-packaged and sold this way.
- List Rental, Licenses and Data Syndication: Some datasets are perfectly suited to being licensed or syndicated for a whole new set of buyers. These tend to bring in respectable revenue and are worth the effort to prepare the data and usage agreements necessary to make this kind of deal work.
- DaaS: Data as a Service is a powerful way to optimize access to and sales of your data, if you have the technical skill and financial will to build and maintain it. Pricing models range from delivering set quantities for a given price, or on a pay-per-use or pay-per-record basis. Some of the above mentioned BI platforms market their capabilities as DaaS though not everyone sees their offerings in this light. For serious data suppliers, DaaS can be a very lucrative option. According to Forbes, “DaaS benefits include the ability to move data from one platform to another, the lack of repetitive and multiple versions of data, outsourcing of the presentation aspect of data storage, easy collaboration and accessibility from any location and any device.”
Everyone is overwhelmed with data and the many ways to maximize its value and the revenue you can earn from it. To do a rapid self assessment of how well you’re using your data, answer a few questions on our scorecard.
All data assets have value. Learning which assets offer the greatest value is an important consideration to maximize revenue and the strategic use of your data assets. To gauge the value of your own data assets, answer a few questions on our scorecard and see how your data stacks up.
Your data is almost certainly not earning as much revenue as it could be. Explore all the options for monetizing your data and treat it like a high value revenue producer. If you’d like a Data Appraisal to definitively value your data assets, please contact us and we’ll get to work.
In the hands of skilled analysts, visualizers and writers, your data can be repackaged into powerful sales, marketing, customer success and PR materials. The team at Chrysalis are experts at this and we’re happy to give you lots of free ideas and help to get you started. Contact us!
Having a great BI package with gorgeous dashboards is not the same as telling stories throughout your organization with data. If your BI package isn’t reaching or being used by everyone it should, consider it an indicator that you need to do more with your data to engage your teams. If you need some fresh ideas for that, contact us – we’d love to help.
Even the big guys are struggling to keep up with the changing market dynamics, business models, technologies and approaches to managing, monetizing and utilizing their data. Doing this work – and only this work – for clients is the very reason that Chrysalis was founded. If you’d like to kick around ideas, contact us any time.