Building an Analytics-driven Organization
Artificial Intelligence, Big Data

Building an Analytics-driven Organization

“Most organizations lack the required skills, technical capabilities and culture to truly exploit their information for an advantage”
- Sue Trombley, MD of Thought Leadership, Iron Mountain

In the analytics hype cycle, enterprises often treat advanced analytics as just another technology wave and quickly jump into procuring tools and implementing big data infrastructure to power their analytics projects. However, despite making significant investments in analytics solutions, many enterprises fail to see any tangible impact.

The reason? It’s often forgotten that analytics is not just about data, tools and big infrastructure and neither knowledge nor technology in isolation can provide insights to solve business problems in the analytics world.

Rather, analytics is a data driven problem solving process, which involves using relevant data and applying right machine learning and statistical techniques to gain insights into a business outcome that helps you to make the right decision.

Simply put, the key to building an analytics-driven organization focus on building analytics-ecosystem that cultivates people applying analytics-driven decision making across the value chain while incorporating the technology and tool effectively.

Analytics Success Demands a Shift in Thinking and Approach

So where do you start? In our daily conversations with clients we find that most people think about this in terms of their available data assets: “What data do I have? and What can I analyze” . This is the traditional way of looking at data or a “bottom-up” approach. But in trying to swift through large volumes of data without first asking the questions, your business goals and problems that you’re trying to address become secondary.

Analytics thinking requires an alternative approach that starts with top of the decision pyramid. It starts with the decisions you want to make, followed by the questions that need answers a.k.a insights. Then, you find the type of analysis needed to glean insights and Finally, you collect the data that can equip you with this knowledge.

Steps to Build Analytics Driven Organization

That said here are some steps that one may use to build analytics driven organization while driving the business value and ultimately build an analytics-ecosystem that cultivates people applying analytics-driven decision making across the value chain over time.

  1. Outcome Linked: Identify pilots or projects that generate value towards a specific outcome or solve a specific problem. Let’s take healthcare for example. In order to improve quality of care, one may start with identifying potentially preventable hospital re-admissions, and get insight into the drivers behind them and develop intervention strategies, ultimately improving the patient care as well as cost of care.
  2. Build Competency: Start with education via boot camps, workshops, formal trainings for C-suite executives, management and teams. Build analytics savvy teams over period of time with a mix of internal and external members as needed. Develop mentors and coaches initially till the organization becomes self-driven.
  3. Make Data Available: Develop a road map for data infrastructure with key focus on making actionable data available for easy access by everyone in the organization who needs it. Therefore, data stops being trapped in silos and the gap between the IT department and lines-of-business gets bridged. This helps create an analytics-driven culture where exchange of meaningful information drives business intelligence.
  4. Build Service Delivery Capability: Provision right tools for the right audience, e.g. SME/Citizen, Vs. Data Scientists and create an elastic infrastructure to scale. Look for reusable templates that allow data scientists to develop workflows and analytics models, which can be repeatedly used by others in the organization.
  5. Collaboration and Cross Training: Create forums for shared use cases, learning, individual interactions and foster change agents. This will help you modify and improve through constant collaboration and training.
  6. Build Measurement Framework: Build a measurement system to track the value internally and bench mark with external metrics.

Bottom Line

Too often, organizations lose sight of their business-critical goals while being tempted to boil the ocean with massive big data implementations, multitude of tools and competencies, which fail to deliver business value. Top-down thinking can be a starting point to solve this issue. Intuceo is here to further help you to jump start your journey toward building an analytics driven organization.

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