Business Intelligence and the Essence of Subscription Data Services

A diverse array of revenue data reveals an industry on a solid upwards growth curve.

Source: Bigstock

I once spent a year heading a division at a business intelligence company. I managed a team of researchers who collected data on local entertainment events. Storytime at libraries, bands at local pubs, sports matches, theater, charity 5K runs, art openings, museum exhibits, church festivals, and major acts of every variety — if it took place in a market we covered, we collected it. After editing and entering into a custom database, we sent this data out to customers — such as newspapers and websites that wanted to offer calendars of events to their readers — who paid us monthly for access to our data in a format or feed they could use.

We collected data, added value to it, and sold it to our customers on a recurring basis. That’s business intelligence. It was a very tiny dataset, compared to the immense amount of data collected across the globe each day, but our data had value for the clients we served.

The idea behind big data and business intelligence is that the modern age encourages the collection of incredibly vast amounts of information on how people, businesses, and the world behave. According to XSI, “there are currently 2.5 petabytes of data generated on a daily basis, which adds to the ever growing magnitude of 2.7 zettabytes currently sitting in data warehouses and silos across the world.”

What we do with that data, and especially how we derive value from it, is at the heart of the enterprise.

Big data is just the start. The challenges are collecting, storing, analyzing, sharing, searching, and updating information. Doing big data right means volume, variety, velocity, veracity, and value.

But the universe of how researchers, companies, and governments use big data is itself quite large. How large? Take a look at this forecast of future worldwide revenue:

(Source: Wikibon; SiliconANGLE, via Statista)

However, it is important to note that this big data graphic does not include the revenue or value that companies gain from using big data; it is merely the revenue gained by supplying those companies. Look at this breakdown of the same data, from the same source:

If you look at this set of graphs, you see that “big data” is here defined as services, hardware, and software that is sold to companies who are using those resources to “do” big data. That is, this revenue reported is the revenue earned by vendors and suppliers. This is NOT the actual value created by big data programs.

Let’s talk about how to get at the actual value of big data, rather than the revenue earned by big data solutions providers. First, as one example, consider streaming video services, as described by InsideBigData.com:

  • Streaming services like Netflix, Hulu, and Amazon are some of the biggest implementers of big data analytics today. By recording consumer behavioral data like searches, ratings, the date and time a program was watched, what device the program was watched on, etc., these companies are able to obtain massive collections of data that are directly useful to them.

This is big data at its core, but it is not outward-facing. What’s the value of Netflix’s big data efforts, separated from the value of the shows it licenses to stream, or the original content it commissions, or the goodwill it has earned by satisfying subscribers? Maybe that’s something that the number-crunchers in the head office think about, as they calculate the ROI on whatever it is they pay Oracle or IBM or whoever helps them do big data. But you and I will never know.

On the other hand, we can say with confidence that companies will pay about $42 billion in 2018 for hardware, software, and big data solutions. And that companies would not do so if the return were not worth it. Maybe companies create value worth 10% more than they spend. Maybe they create value worth double their spend, or ten times what they spend. The bars on that total revenue graphic above? Please think of them being even longer. And however long they are, the forecast is for growth — that at least is clear from the infographics above.

However, there is more to big data than the unknown inner workings of the Netflixes and Amazons of the world. There are the local event listings companies, and even more interestingly, there are the Bloomberg terminals, the Dun & Bradstreet reports, and the subscription services from firms including EquiFax, Thomson Reuters, Lexis-Nexis, and Informa. All of these are companies selling access to big data, and all of them have revenue derived directly from subscriptions to that access.

I worked for a trade organization of business publishers several years ago, and when I worked there, I compiled a periodic estimate of the actual revenue generated by trade publishers who were (and are) moving into business intelligence subscription services. I looked at Northstar Travel Media’s hospitality and travel data offerings. And at Farm Journal’s AgWeb and agricultural commodity data services. And at Hanley Wood’s Metrostudy Construction Industry Database business.

The most recent b-to-b trade media revenue report put out by that trade association, released last year, reports 13% growth in data and business information, making it the fastest growing segment of a flat total trade media industry. That growth rate is the story that needs to be told.

I also have three different global forecasts that are more limited in scope, to pure business intelligence applications. I suspect they too really only cover business intelligence service providers, but again, the important takeaway is not the revenue total but the direction of growth.

(Source: Various sources, including Shea & Company, compiled by Statista)

The other two projections, showing similar results, are here from Gartner and here from Apps Run The World. All the infographics and data I have sourced seems to confidently project significant positive annual growth for the segment. The Gartner report, released last year, has more to say about long-term growth in business intelligence (“BI”):

  • Modern BI and analytics continues to expand more rapidly than the overall market … The modern BI and analytics market is expected to decelerate, however, from 63.6 percent growth in 2015 to a projected 19 percent by 2020. Gartner believes this reflects data and analytics becoming mainstream. … Organizations will benefit from the many new and innovative vendors continuing to emerge, as well as significant investment in innovation from large vendors and venture capital-funded startups.

While we’re on the topic of the vendors who supply hardware, software, and services to companies for their big data initiatives, let’s take a look at who they are:

(Source: Gartner, JPMorgan Chase, via Statista)

If there is a lesson to learn from these names, it is that big data vendors are among the most respected tech companies out there, another sign that business intelligence is a profitable area for future growth. Also, the lack of a clear market leader bodes well for competition-fueled innovation and experimentation. [Let’s just hope that competition and the AI tools needed to master big data do not lead to a runaway bootstrapping general artificial intelligence crisis, as I detailed a few weeks ago.]

Whether you are already selling data subscription services or just thinking of how to get started, it is useful to know why your potential clients need access to the data you sell. Consider this analysis of the benefits customers expect:

(Source: Harvard Business Review, via Statista)

Top three things business intelligence can do for you: improving the quality of decisions, improving planning and forecasting, and consistent data across the enterprise. Evidently, the benefits are huge. Well, color me a bit skeptical. Nearly all of the benefits offered seem good to a majority of the 374 random American corporate execs polled. The source on that is Harvard Business Review, but please note that the original report was sponsored by Oracle.

Well, leave aside the benefits. Let’s ask executives to identify the real drivers of adoption of business intelligence solutions:

(Source: Statista estimates; Forbes; Dresner)

Who was polled on this one? Survey respondents came primarily from IT (28%), followed by Executive Management (22%), Finance (19%), Sales/Marketing (8%) and the Business Intelligence Competency Center (7%). And who are the drivers? Mostly the C-suite, operations, sales, and finance people … that is, the ones who do not get under the hood. Unsurprisingly, the IT pros who will have to implement big data were more guardedly optimistic.

And what are the challenges that concern those IT pros?

(Source: NewVantage Partners via Statista)

I like this graphic, which says that there is division within companies on how to use data. In addition, the effectiveness of business intelligence solutions is hindered by managers who do not understand it, as well as by sheer mule-headedness, poor strategy, and staff who are not on board with the vision.

And this, above all, offers some insight for those who seek to sell data subscription packages. To make the sale, you have to overcome the understanding gap and you have to offer tactics and strategy and instruction on how to use your data.

Insider Take

The growth rate for business information revenue has been strong, and the predictions for future growth seem solid. The utility of business intelligence data, in general, should be obvious. Nonetheless, data publishers need to teach their clients how to use their data offerings, and they sometimes need to hold their hands while leading them to the value proposition.

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