Data-Driven Process Improvement
September 04 – September 08 \ 2022: Kuwait
September 18 – September 22 \ 2022 : Amman
October 02 – October 06 \ 2022 : Kuwait
October 16 – October 20 \ 2022 : Amman
October 30 – November 03 \ 2022 : Kuwait
November 06 – November 10 \ 2022 : Amman
Introduction
By the end of this course, learners are empowered to implement data-driven process improvement objectives at their organization. The course covers: the business case for IoT (Internet of Things), the strategic importance of aligning operations and performance goals, best practices for collecting data, and facilitating a process mapping activity to visualize and analyze a process’s flow of materials and information. Learners are prepared to focus efforts around business needs, evaluate what the organization should measure, discern between different types of IoT data and collect key performance indicators (KPIs) using IoT technology. Learners have the opportunity to implement process improvement objectives in a mock scenario and consider how the knowledge can be transferred to their own organizational contexts.
Material includes videos, demos, project work, readings and discussions. This course is ideal for individuals keen on developing a data-driven mindset that derives powerful insights useful for improving a company’s bottom line. It is helpful if learners have some familiarity with reading reports, gathering and using data, and interpreting visualizations. It is the first course in the Data-Driven Decision Making (DDDM)
Objectives
Attending this IACT training course will give delegates an opportunity to:
Þ Develop a plan to align operational and performance goals
Þ Devise a data collection strategy and validate data integrity
Þ Understand how to create current and future state process maps
Þ Prioritize data gaps for root cause analysis
Who should attend this Course?
Ü Individuals keen on developing a data-driven mindset that derives powerful insights useful for improving a company’s bottom line
Ü Data scientists
Ü Data analysts
Ü Business intelligence analysts
Ü Business executives
Ü Ambitious managers
Ü Aspiring entrepreneurs
Ü Financial analysts
Course Methodology
The course uses self-assessments and a wide mix of business cases that promote healthy discussions around the importance of managing multiple tasks, deadlines and priorities. Participants will benefit from role plays covering workplace challenges related to handling tasks, deadlines and priorities. They will learn how to deal with conflicts that may arise as a result. Interactive team exercises are also used with each team presenting their findings and comments.
This interactive training course includes the following training methodologies as a percentage of the total tuition hours:
- 30% Lectures, Concepts, Role Play
- 30% Workshops & Work Presentations, Techniques
- 20% Based on Case Studies & Practical Exercises
- 20% Videos, Software & General Discussions
Pre and Post Test
Outline
DAY 1:
Deciding your data need
Þ Using data to improve your decisions
Þ Challenges related to self-service data
exploration
Þ Asking key business questions first (KBQs)
Þ The power of clear Key Business Questions (KBQs)
Þ How to ask the right Key Business Questions
Þ Curating the most important data insights
DAY 2:
Using data to understand your custmers and markets
Þ How this butcher uses data to understand customers
Þ Netflix use case - vs Disney - this is why Disney launched Disney +
Þ Amazon use case
Þ The increasing need for real-time data to understand customers and markets
DAY 3 :
Using data to provide more intelligent services
Þ Using data to make more intelligent products
Þ Using data to improve your business processes
Þ Monetising your data - intro
Þ The Shotspotter case study
DAY 4 :
Sourcing and collecting data
Þ Defining data use cases walk through (part 1)
Þ Defining data use cases walk through (part 2)
Þ Defining data use cases walk through (part 3)
Þ Secton intro
DAY 5 :
Structured vs unstructured data
Þ Internal vs external data
Þ Different types of data
Þ Meta data
Þ The importance of realtime data
Þ Gathering internal data
Þ Accessing external data
Þ Sources of external data
Þ When the data you want doesn't exist
Fees:
The Fee for the seminar, including instruction materials, documentation, lunch, coffee/tea breaks & snack is:
3.750USD$
Schedule:
08:30 – 10:15 First Session
10:15 – 10:30 Coffee Break
10:30 – 12:15 Second Session
12:15 – 12:30 Coffee Break
12:30 – 14:00 Third Session