In many ways, building a business case for content and text analytics software is the same as with any enterprise application. For example, the content analytics business case often depends on having an influential executive sponsor who can champion the cause internally and help demonstrate how the technology can deliver real value to the business.
But in addition to the traditional legwork around business and management buy-in, content management analysts and professionals said that there’s typically a far greater educational component to selling organizations on content analytics investments because the technology is unfamiliar ground for many people.
“One of the more common challenges is the need to educate management about what the benefits of text analytics will actually be,” said Fern Halper, an analyst at Hurwitz & Associates, a consulting and market research firm in Needham, Mass. “A lot of times, companies will not get the difference between [enterprise] search and text analytics, so there’s a big education element to the business case.”
In the example highlighted by Halper, proponents need to spell out how text analytics goes beyond locating documents or other forms of unstructured information in corporate systems, enabling business users to analyze textual data in an effort to uncover patterns and glean insights about the content. Before any such crash course begins, however, someone needs to take the lead on determining specifically how text analysis software could be used to help transform an organization’s unstructured data into a valuable competitive asset.
More often than not, Halper and other analysts said, that leader will hail from the business ranks, not from IT. Or else the process could be orchestrated by an external consultant with content analytics expertise. In either case, business users should be involved in assessing the technology’s potential usefulness for things such as avoiding business risks, spotting new revenue opportunities and enabling workers to do their jobs more effectively.
Social media data: A good fit for content analytics?
Increasingly, tweets, Facebook posts and other social networking comments are the catalyst for content and text analytics programs, as companies look to track and make sense of what customers are saying about them online. But analyzing such data without a purpose isn’t the right approach, according to Seth Grimes, president of consulting firm Alta Plana Corp. in Takoma Park, Md.
“The way a lot of companies get started, which we don’t recommend, is beginning with the perception that they need to tap into all this social media data. But the problem is they have no idea what to do with the information they find,” Grimes said. “They need to first figure out how all this information affects the business and how [analyzing] the information can improve the business in some way.”
At Tribune Co., there was a pretty clear picture from the get-go of how a text analytics program could translate into real business value, according to Keith DeWeese, director of information and semantics management at the Chicago-based media organization. But that picture had to be painted for a broad user audience, he noted.
When Tribune began planning the text analytics deployment about five years ago, it was lagging behind competitors in creating new online-news products, pushing out relevant content to readers and properly tagging and configuring content to help increase page views and Web traffic. “We had to analyze tens of thousands of articles a day and we didn’t have the luxury of hiring hundreds of human indexers to go through content all day,” DeWeese said. “We knew we had to get a tool in to help us do this.”
With a variety of key people in editorial and corporate management already on board, the text analytics project champion – Tribune’s vice president of products – did roadshow after roadshow to educate users throughout the company’s far-flung operations on the software’s potential uses and benefits. The trick was focusing on the core business value and making the technology accessible, DeWeese explained. “The heavy-duty technical stuff had to be translated into something very understandable for the average busy executive who doesn’t have a lot of time to go down the road of learning what taxonomies and ontologies are,” he said.
Don’t overthink the content analytics business case
In making the business case for content analysis software, another good idea is to keep it simple, with perhaps five to seven key points, advised Theresa Regli, an analyst at content management consulting firm Real Story Group in Olney, Md. “People spend a lot of time and money doing a business case, but you really just have to think about what matters most to the organization and what are the things that will make it most effective,” Regli said.
At some companies, a formal content analytics business case with an up-front return on investment (ROI) analysis might take a back seat to more organic adoption if a pilot project is successful in one part of the business, prompting other departments or business units to want to follow suit.
Halpern saw signs of that in the results of a survey on text analytics adoption conducted by Hurwitz several years ago. Of the more than 75 respondents to the survey, only about half said they did an ROI analysis before buying text analytics software. Of the group that moved forward without ROI calculations, most said they had a pressing business problem – for example, competitive pressures, the need for improved decision making or regulatory compliance issues – that trumped the idea of spending time building a formal business case.
But even if the adoption of content analysis tools initially takes root organically, Halpern and other analysts recommend going back and doing a full ROI analysis after the software is in use. Without one, they said, a content analytics program is more at risk for abandonment, especially if budgets get tight. It also could be more difficult to win approval for expanding a deployment to encompass other departments or data sources.
At Tribune, building the business case and managing expectations for the text analytics implementation has been – and likely will continue to be – an ongoing exercise. “We always have PowerPoints in various degrees of readiness,” DeWeese said. “You have to keep the momentum going. You can’t say, ‘Now we did it,’ and just sit back. There’s always something else coming down the pike, and you have to keep making the case that this is important.”
ABOUT THE AUTHOR:
Beth Stackpole is a freelance writer who has been covering the intersection of technology and business for 25-plus years for a variety of trade and business publications and websites.