Using Data to Drive Strategy

American Management Association

How long?

  • 2 days
  • in person

American Management Association

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Who should attend

Non-technical managers who want to take advantage of data as a tool to make evidence-based decisions.

About the course

Get the skills to turn data into revenue

Whether you want to attract new customers, improve products, forecast sales or streamline operations, your decisions are much more effective when you put data to work for you.

What will you get when you use data to drive strategy? Higher revenue, and reliable and consistently predictable business results. Insights that become new ways of doing business. Quick and effective strategies to proactively navigate change. This course is your ticket to shift to higher gear and elevate you and your team to rise to a new level of success.

How You Will Benefit

  • Pinpoint key performance indicators to move from analysis to profit
  • Make decisions that are backed up by verifiable data
  • Apply data analytics to reach strategic goals with greater precision
  • Communicate analytic information and complex ideas more effectively
  • Confidently analyze business data and build robust business models
  • Use data to set direction for your own business units and teams
  • Drive business strategy, including forecasting and assessing competitive risks
  • Drive value, improve services and build your competitive edge
  • Incorporate data and technology as a part of how you do business

What You Will Cover

  • Understanding how data is driving strategy
  • Changing and adapting to evolving and emerging trends
  • Getting into the mindset and applying the characteristics of data-driven management
  • Building a team that’s highly curious, pragmatic and open to new ideas
  • Taking a systematic approach to data: framing the question, finding and shaping the data, and selecting the right variables
  • Comprehending data, big data, artificial intelligence and machine learning
  • Choosing the right data to track your key performance metrics and support your decisions
  • Using basic data analysis tools to interpret data sets
  • Extracting business insights using descriptive statistics, predictive analytics and descriptive analytics
  • Building business models and communicating results: decision and forecasting models, performance dashboards
  • Communicating complex analysis and ideas using tools and techniques
  • Framing results that drive decisions
  • Understanding decision-making traps and biases
  • Practicing making data-driven decisions
  • Setting data-driven objectives: prioritizing data, translating data into measurable metrics, selecting KPIs, setting objectives, forecasting, and assessing risks
  • Building a data-driven team: recognizing and overcoming barriers to adopting a data-driven management culture
  • Applying strategies to facilitate personal and organizational change

Outline

Learning Objectives

  • Explain How Data-Driven Technologies Are Changing How Organizations Interact with Customers and Employees
  • Describe How Data-Driven Technologies Are Changing Roles
  • Use Desktop Tools Like Excel to Analyze Data Obtained from a Variety of Sources to Answer Business and Performance Questions
  • Build Robust Business Decision Models
  • Communicate Analytic Information More Effectively
  • Use Data to Set Direction for Your Own Business Units and Teams

How Data Is Driving Strategy

  • Explain Key Trends in Data and Technology and How They Are Changing Organizations—the 4th Industrial Revolution
  • Describe How Exponential Change Is Impacting Organizations
  • Identify Ways That Technology and Data Access Are Driving Business Strategy and Competitive Tasks

Why Data-Driven Decision Making?

  • Why Data-Driven Decision Making?
  • Understand Decision-Making Traps and Bias
  • Recognize Personal and Organizational Barriers to Change
  • Develop Leadership Strategies to Facilitate Change

Taking a Systematic Approach to Data

  • Utilize How to Use the DASA Model to Think Systematically About Data
  • Set Priorities for Data Analysis for Data Analysis
  • Recognize the Types of Data You Use
  • Locate Where to Find the Data You Need
  • Prepare Data for Analysis

Data, Big Data, and AI

  • Identify the Data You Will Use to Track KPIs
  • Use Basic Data Analysis Tools Available in Desktop Applications to Analyze Data Sets of Up to One Million Records
  • Select the Right Tools for the Questions You Need to Answer
  • Define Big Data and Explain the Various Types
  • Compare AI and Machine Learning and Describe How Each Is Applied

Building Models and Communicating Results

  • Use Data to Make Predictions
  • Build Decision Models
  • Create Performance Dashboards
  • Use Best Practices to Help Communicate Complex Analysis and Ideas

Making Data-Driven Decisions

  • Use Data to Support Decisions
  • Use Tools and Techniques to Communicate Data and Analysis More Effectively

Setting Data-Driven Objectives

  • Prioritize Data Needed to Support Objectives
  • Utilize Techniques to Translate Customer and Business “Wants” into Metrics You Can Measure and Analyze
  • Select Data for KPIs
  • Utilize Best Practices to Set Data-Driven Objectives
  • Utilize Data-Driven Objectives to Forecast and Assess Risk

Building a Data-Driven Team

  • Identify the Kinds of Challenges You Will Face When You Begin to Change Your Behavior and Your Team
  • Identify Tools and Techniques You Can Use to Help Facilitate Personal and Organizational Change
  • Recognize and Overcome Organizational and Business Barriers to DataDriven Decision Making

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Using Data to Drive Strategy at American Management Association

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