Front-runners for Business Intelligence Investments in 2017
Every year at this time, I look forward to insights from Twitter participants in our Friday #BIWisdom tweetchats to glean their “boots on the ground” perspectives of what’s new and what has abiding interest for the upcoming year in enterprise BI investments and intentions. At a couple of recent tweetchat sessions, I asked the #BIWisdom group some questions about technologies and initiatives for 2017 related to BI and analytics.
I asked the group whether they think information catalogs to support self-service will be an important theme in 2017. I suspect a challenge in an organization of size is simply "finding stuff" and a lot of time is wasted searching for data, models, reports, etc. or duplicating efforts.
They noted that most companies’ focus on self-service depends less on investment than on increasing collaboration between IT and the business. One participant tweeted that she hopes 2017 will be the year that the business users and IT groups coordinate regarding self-service. And someone added it’s still common for IT and business users to have divergent goals and even definitions of self-service BI. Another participant tweeted that companies need easier self-service analytics, and that is tied to “a relentless focus on usability and better exploitation of collaboration in the context of BI.”
Natural Language Analytics (NLA) and Natural Language Processing (NLP)
In December 2016, we released the report on our first annual market study of NLA in BI. This is an area that has been around for quite some time in BI but has not yet fully emerged. But with the advent of Siri, Alexa and GoogleHome, this is a hot area. Will 2017 see a big movement in NLA?
The group’s consensus opinion aligned with our market study report – NLA and NLP adoption are greater than a few years ago, but they are not yet mature. One participant tweeted that he had seen some novel demos but few practical use cases have been implemented.
Still at a nascent level in BI, some of the #BIWisdom tweetchat group were not sure who are target users for NLA / NLP in a business context. Another participant responded that users would be “anyone having to write a report – business analysts, accountants, etc.” Our market study revealed that the main interest for this capability is among less technologically savvy users.
The group agreed that, although probably not in 2017, NLA / NLP could be the next “big thing” for certain BI applications and users.
I reminded the tweetchat group that big data use cases now exist and there were big increases in adoption in the business intelligence space in 2016. I asked whether they think big data will continue to be an important investment for organizations in 2017. And will the term “big data” finally become just “data?”
It’s still distinct but is becoming mainstream, someone tweeted. Technologically, big data is different, but it’s becoming more functional. Another #BIWisdom member tweeted that the demands for better data governance should continue because of big data. However, much of governance depends on people and process.
Will budgets for business intelligence and analytics increase for #2017? Some of the group agreed that they expect investments in BI education, software, consulting and new hires to be the same in 2017 as it has been for the past few years. Others indicated overall investment in BI is increasing at their company, primarily because of the need to refresh hardware and software. No one indicated a decrease in spending for 2017, and one member commented that “BI is seen as table stakes” in his company’s industry.
Bottom Line: My final question to the #BIWisdom group was “What still limits BI deployment or use in 2017? Is it cost? Lack of investment?” They responded that the biggest limitations they encounter are (1) the difficulty in governing data, tools and applications and (2) issues around perceived vs. real value.
With a greater emphasis on self-service BI functionalities this year, governance becomes even more crucial. This is not a new issue; in fact, I blogged in 2014 about whether it’s possible to have self-service BI and governance too. Although data discovery tools enable line-of-business user insight, companies need to maintain centralized control to ensure proper usage of data. Establishing a Business Intelligence Competency Center (BICC) is an effective way to ensure self-service BI does not become a company vulnerability.
When it comes to BI value, survey respondents in our annual Wisdom of Crowds® Business Intelligence Market Study, consistently state that making better decisions is their primary goal for business intelligence. Achieving this goal is the value or return on investment, and it manifests itself in two financial aspects: cost savings or revenue generation. However, some companies are not successful in achieving these goals. I’ve blogged in the past about two related challenges – dangling BI initiatives and ineffective Key Performance Indicators (KPIs) used to communicate a BI strategy.
I think a great resolution for 2017 is to end BI’s deployment limitations, and I’ll check back with the #BIWisdom tweetchat tribe in December for opinions and examples of companies making progress in this goal. Meanwhile, please feel free to contact me with your own success stories through this year.
Howard Dresner is president, founder and chief research officer at Dresner Advisory Services, LLC, an independent advisory firm. He is one of the foremost thought leaders in Business Intelligence and Performance Management, having coined the term “Business Intelligence” in 1989. He has published two books on the subject, The Performance Management Revolution — Business Results through Insight and Action, and Profiles in Performance — Business Intelligence Journeys and the Roadmap for Change. He hosts a weekly tweet chat (#BIWisdom) on Twitter each Friday. Prior to Dresner Advisory Services, Howard served as chief strategy officer at Hyperion Solutions and was a research fellow at Gartner, where he led its Business Intelligence research practice for 13 years.