Data-Driven Decision Making and Innovation

Explore the DIKW-D model and its role in framing data driven decision making, preparing your mind for reflection while acknowledging its high level, theoretical nature.

Define a north star vision for data-driven evolution using data-use maturity frameworks, align resources, and guide decisions from gut feel to autopilot data-driven decision making.

Learn data use maturity frameworks to guide strategic planning from data awareness to data-driven decisions, featuring standardized reporting, dashboards, self-service visualization, and predictive, prescriptive analytics and autonomous systems.

Apply data maturity frameworks to drive alignment and planning, select and adapt frameworks with colleagues, and probe who supports or resists data driven decisions to map your path.

Learn how to control and influence data driven decision making by understanding the nine phases of the process, including the big data challenges of volume, variety, velocity, and veracity.

Define your objective, transform data into information, and generate insights to create alternative options. Decide, act, and measure outcomes to gain new knowledge and wisdom for future decisions.

Examine the ikat d model and human wisdom in decisions, explore data use maturity frameworks, and master the nine-step data driven decision making process for better outcomes.

Identify the key components: data use strategy, technology, people, and leadership that prepares an organization to become data driven.

Learn to craft a clear, compelling data use strategy aligned with business objectives by applying the business model canvas and the 10 types of innovation to unlock real benefits.

Explore crafting a clear data use strategy and a relevant problem statement, using the business model canvas to view the nine building blocks and align data plans with business strategy.

Apply the business model canvas to map value proposition, customer segments, channels, revenue streams, activities, resources, costs, and partners to a data-driven decision making strategy, illustrated by Red Roof Inn.

The business model canvas starts data-use strategies but requires what and why; align teams, set clear objectives with smart goals, create multiple strategies, and secure senior leadership buy-in.

Apply the ten types of innovation framework to see how data drives breakthroughs across profit model, network, structure, product performance, product system, experience, channel, brand, and customer engagement.

Explore how to craft clear data use strategies aligned with existing objectives, validated by gap analyses and stakeholder interviews, and supported by executive buy-in and the data driven decision making process.

Explore how technology supports data-driven decision making by transforming raw data into information and insights, and learn to engage technical experts to optimize data use strategies.

Identify the technical and non-technical roles responsible for delivering outcomes across the nine steps of data-driven decision making, from raw data to actionable insights.

Explore three analytics team structures—centralized, bespoke, and hub-and-spoke—and see how analytics as a service, cross-cutting functions, and dedicated data and insights teams shape engagement and efficiency.

Conclude chapter two by stressing that a clear, compelling strategy aligns stakeholders and drives early success, while technology enables data to insights rather than solving everything. The talk emphasizes that people and leadership, not tech alone, shape analytics outcomes, dictate team structure, and keep the data-driven process on track toward future chapters.

Explore the data driven mindset of individuals and leaders, and the beliefs and behaviors that cultivate a data driven decision making culture.

Believe in the power of data and champion data-driven decision making. Communicate insights, align teams, and model data use to show you can make a difference.

Foster authentic inquisitiveness and empathy to understand what data reveals, why it changes, and how mechanisms and levers drive outcomes. Ask strategic questions to shape data use strategies.

Adopt a customer-first data-driven mindset by acting as a service provider to internal and external customers, democratizing data access, and delivering self-service solutions that address context and needs.

Adopt a data advocate mindset, stay inquisitive about what data says, and embrace experimentation to learn while maintaining a customer focus; explore the five mindsets and their behaviors.

Drive data-driven decision making by advocating in meetings and workshops, asking what data we have and need, sharing case studies, and supporting data-related processes to unlock faster, cost-saving decisions.

Apply data-driven behavior by asking probing questions about data quality, data warehouses, data transformations, algorithms and modelling techniques, while assessing probabilities, biases, and encouraging further exploration.

Lead data-driven decision making by running pilots with clear hypotheses to learn quickly; celebrate all outcomes, pivot on insights, and act on what you learn.

Apply behavioral science and user design methods to understand customer mindsets, use inclusive workshops and interviews to uncover routines, unlock data-driven value and benefits.

A data driven leader implements talent and technology, aligns decisions to the organization’s strategy, and fosters data storytelling and inclusive workshops to drive informed, strategic investments.

Celebrate completing this data-driven decision making and innovation course, built on research and interviews. Reflect, critique, and apply insights with peers and your organization.