It is crucial for enterprises today to shift their organizations from being data-driven to being insight-driven, according to executives from MicroStrategy and Forrester Research.
“We’re only accessing a subset of all the data available, yet the amount of data that we collect continues to grow” very quickly, Hugh Owen, SVP of product marketing at MicroStrategy, said Aug. 21 during the webinar “Transformation with Data: The Journey to the Intelligent Enterprise.”
To transform, organizations must be able to quickly build intelligence applications on top of their data and enterprise assets, he said.
“Agile business models,” meanwhile, are the “key to success” in this “age of the customer,” Boris Evelson, VP and principal analyst at Forrester Research, said, pointing to recent studies that showed a strong correlation between agility and overall business success. It’s also important for organizations to modernize their business intelligence (BI) data architecture, he said.
Evelson started hearing in 2008 that organizations were drowning in their data and “starving for insight” from all that data, he said, adding he’s still hearing that from most clients. But “this is probably one of the most difficult challenges to overcome,” he said.
The number of companies storing more than 100 Tb of data nearly doubled in 2017, but we only get insights from a small subset of all data available, he said. “We still have a long, long way to go” because only about 10-20% of a company’s data – structured and unstructured, internal and external — is typically being used for analytics and insight, he pointed out.
Yet insights-driven companies are growing at an average of more than 30% annually and are on track to earn $1.8 trillion by 2021, according to Forrester Research, he noted. Through 2021, such companies will be growing 8-10 times faster than their non-insights-driven rivals, he projected, adding: “You cannot afford to be on the losing side of this picture.”
Most mid- to large-size global, multi-product line companies have “already become data-driven,” meaning they have some sort of data management infrastructure and have created some sort of analytical-derived data sources, he noted, adding: “You’re getting a lot of signals from your data, but are you really transforming these signals into actions and are these actions driving tangible business outcomes?”
BI platforms using artificial intelligence (AI) can provide organizations with much deeper insight, he said.
“AI is not single technology, but rather it’s a collection of about 12 different technologies, and a lot of them have been around for years,” he pointed out, noting machine learning (ML) has been used for more than 30 years, while neural networks have been built for more than 20 years.
What’s different now, however, is that computing power has increased, allowing for scale and AI to be put to general-purpose enterprise use, he said.
Over the next decade, however, AI won’t replace managers, but managers who use it will replace those who don’t, he predicted. Similarly, over the next decade, AI won’t replace BI, but BI tools that use AI will replace those that don’t use AI, he predicted.
ML is playing an increasingly important role in BI platforms and one positive sign is that ML is now combining insights from structured and unstructured data, “so we’re definitely going in the right direction,” he said, adding it’s also important for organizations to move their BI to the cloud.
During the webinar, MicroStrategy’s Owen also pointed to some of the findings from his company’s recently-released 2018 Global State of Enterprise Analytics Report. For example, according to the findings of a survey conducted for MicroStrategy by Hall & Partners, the top three barriers to more effective use of data and analytics within organizations today are the current solution being too complicated (according to 28% of respondents), access to data being limited across an organization (33%) and data privacy and security concerns (49%).
Also, the top three benefits that organizations realized through their analytics use were improved efficiency and productivity (63%), faster, more effective decision making (57%) and better financial performance (51%), Owen said.
Over the next five years, the trend expected to have the greatest impact on organizations’ analytics initiatives is expected to be cloud computing, he said, pointing out that 24% of respondents cited that. It was followed by big data at 20%, artificial intelligence and ML at 18%, the Internet of Things at 16%, digital identity management at 12%, blockchain at 7% and voice/natural language generation (NLG) at only 3%.