The Final Stretch in Big Data Management: Driving Business Value for Enterprises
Big Data presents huge opportunities for business if they know how to understand and share it.
In a recent survey we conducted of over 200 UK business leaders, the average response (on a scale from 0 - 10, 0 being completely disagree, 10 being completely agree) to “I frequently stage debate between analytics and business skill sets” was a 4.65. Leaders aren’t focused on effectively connecting analytics with business, and this needs to change.
At Connectworxs, we have spoken to over 1,000 leaders and experienced first-hand the challenges that organizations face in their efforts to truly realize the business value of Big Data.
The crucial step to driving positive business outcomes lies in the final stage of our data maturity model: connectivity of an organization and its teams.
Simply put, this is the ability of teams to connect business experience with advanced analytic skills while facing the most important business challenges each day. This connectivity must then be scaled throughout the entire organization using a simple and shared language. This enables business units to start breaking down data silos, allowing other business leaders to discover insights from teammates while up against the business’s must-win battles.
The Connectworxs Updated Data Maturity Model
Data maturity should not be a challenge that Chief Data Officers face alone, but rather an opportunity for business teams to utilize Big Data to fuel business value in their areas of expertise.
The Data Maturity Model starts with finding the right infrastructure and home for data. This is not a small challenge as organizations are faced with a tsunami of data every day. Data needs to be organized in a secure and well-managed infrastructure so that the front line of the business can gain access quickly when needed.
This starts to build a single source of of data that leaders know they can trust and is linked to driving business value.
2016 NewVantage Partners Big Data Executive Survey
Organizations need to source the right talent. This is about welcoming a new member of the business team who can master advanced mathematics and statistics, data modeling, data mining, predictive modeling, visualization… the list goes on. But most importantly, finding the right talent to interact with business teams and domain experts - to ask tough questions, to ask “stupid” questions, and to understand how this data is going to be used.
“I’ve never heard anyone discuss a data science profile without talking about understanding the business. Again, it’s critical to have the person running the analysis fully understand – and be interested in – why this question is being asked, what the business person would do given the results, and why they would make that decision.”
- Bill Franks, Teradata Chief Analytics Officer
To progress along the line of data maturity, like all successful transformations, quick wins and early success will demonstrate value to the business leaders who are going to lead this journey.
“Light fires” with data project success and let the leadership community in the organization share the story.
Business value is truly accelerated through connectivity within the organization.
In their 2017 Big Data Executive Survey, NewVantage Partners found that the greatest perceived barrier to Big Data adoption is insufficient organizational alignment:
Business leaders must connect data scientists to teams and ask where can we add the most value for those we serve, and how can data fuel transformation. Business and analytics experts should work together to achieve clarity of where data can enhance our shared understanding of business context, and iterating through challenges together through a simple and shared language.
The opportunity to derive tangible business value from Big Data can be realized when organizations can achieve this connectivity at scale.
Connectworxs created the ADAPT Cycle™ to help businesses drive this connectivity between teams and data.
Bill Franks interview: tdwi.org/Articles/2013/10/01/5-Essential-Skills-Data-Scientist.aspx?Page=2