Times have changed in the world of decision making for big companies. Many are now paying much more attention to their internal data to support and guide their business decisions.
In the past, companies rarely slowed down enough to harness their internal data, nor did they have the resources and tools to make the information actionable. As companies are driven by EBITDA growth, capturing and evaluating key operational data has become more important in shaping their strategic decisions.
The trend has clearly emerged as companies utilizing business intelligence and analytics in their planning throughout the year has increased. Ultimately companies want the best data that speaks to their business while providing real-time outputs across customized dashboards. The C-suites’ need for data visualization and reporting against it to their executive boards and upper management is growing. Big data is being used to improve operational efficiency, with the ability to make more informed decisions based on the latest up-to-the-moment information which is rapidly becoming the mainstream norm.
Few people dispute that organizations have more data than ever at their disposal. But actually, deriving meaningful insights from that data—and converting knowledge into action—is easier said than done. There are many challenges organizations face in adopting analytics.
One of the biggest challenges of making the evolution from a knowing culture to a culture that is much more objective and data-driven, and it embraces the power of data and technology—it’s really not the cost. The biggest impediments relate to cultural challenges such as organizational alignment, lack of understanding, and change management.
Another significant challenge for companies will continue to be around data privacy, and what is shared versus what is not shared. Keeping in mind that companies’ consumers are willing to share if there’s returned value. Big data and business intelligence will continue to be the way that companies make decisions in a time of immediate information and need for the ability to run “what if” scenarios while managing risk and rewards.
In a recent survey conducted across many C-suite executives, over half surveyed predict major disruption on the horizon, as big data and algorithms continue to change how businesses operate and compete. Companies that fail to adapt do so at their own competitive and market risk. Data analytics are fast becoming the lifeblood of IT.
Big data, machine learning, and data science — the range of technologies and techniques for analyzing vast volumes of data is expanding at a rapid pace. These tools and techniques gain deep insights into customer behavior, systems performance, new revenue opportunities, and strategic optimal facility locations. Companies can use analytics to find new patterns and insights in the same data their competitors are seeing. Organizations have always collected data on customers, suppliers, products, and services; however, they have not had the tools to analyze and/or visualize for planning. Now, traditional information can be combined with big data (i.e., interactional data) and third-party data that, for example, add demographic and geographic details.
Uncovering data patterns sets the stage for conducting predictive analytics for all companies that elect to invest in the process. Today’s companies are going to continue to make decisions in a more thoughtful way on the back of substantial data and visualization to impact their market.
Eric Beichler is Managing Principal at Mohr Partners Inc.
