John Schwarz founded Visier to address what he saw as the major failing of business intelligence and big data analytics.
Business intelligence and big data analytics, as we know them, have largely failed. Massive value can be attained when businesses use data to understand and optimize their operations, and to outsmart and outperform their competition. But, except for a few giant firms with nearly unlimited IT resources and a strong background in technology adoption, most organizations lack either the expertise or budgets to effectively leverage big data.
Three fatal flaws plague most analytics offerings today:
Flaw #1: They focus on the technology and tools, not on the business questions
Instead of starting with the business questions that technology is required to answer, the focus has been on data management technology. But achieving greater business performance with analytics isn’t about the data. It’s about answering the right questions, which shape the business strategy and lead to better business outcomes.
Flaw #2: They have a long and costly time to value
It can take a year to build a data warehouse, and months more to assemble queries, dashboards, and scorecards. This slow manual process generates outdated insights, which invariably lead to change requests and new questions that can’t be readily answered.
Flaw #3: They lack domain expertise
Analytics engines have been built for the wrong people — IT professionals, data scientists, mathematicians, and analysts — who are in extremely short supply. While these professionals are technical experts, they typically do not have the business experience, insight, or context to know what business questions to ask—or the ability to act on the answers.
Turning analytics upside down
To realize the immense promise and potential of analytics, a fundamentally different approach is needed. And that requires that analytics providers dedicate their focus to business users and their domain-specific questions.
1. Start with business leaders and their questions
Business analytics are about finding answers, discovering new insights, linking insights to decisions, and modeling the probabilities of the future — all with the aim to shape business strategy in such a way that it drives business performance. All of this starts with industry- and domain-specific questions that are directly tied to business performance.
2. Combine technology with business domain knowledge
The birth of applied business analytics combines domain expertise with technological utility. Decision makers should be able to walk through a process of discovery by iteratively asking business questions and attain contextual, domain-specific insights instantly.
3. Modernize the enterprise software business model
Instead of the traditional business model, which has organizations being continually hit by an avalanche of statements of works and development costs, the new approach to business analytics allows businesses to subscribe to a complete, pre-built solution — with all data management included — for a fixed and predictable fee, delivered from the cloud so that all innovation can be instantly shared by all users.
Outsmarting and outperforming with applied business analytics
This new approach to analytics allows organizations to get smarter. It gives them a better understanding of what is working and what isn’t. It shows them cause and effect, how variables are impacting business performance, and the probable outcomes if those variables are adjusted. It provides for real-time learning and instant adjustment, not needing to wait for the next planning cycle.
This is the promise of applied business analytics. And it is attainable today.