Metrics and Analytics for Strategic Decision Making Course

Organizations that lead in analytics using data for information outperforms those who are just beginning to adopt analytics. Potential advertisers on television wants to know number of viewers before deciding to place advert. Data must provide insights, not noise. Population census, survey of any type of report should understand the health of the function, communicate progress, diagnose bottlenecks, drive decision making, predict future progress.

The mode of collection, audience, confidentiality, and analysis help to assist effective decision making. With the wrong data, you get wrong result and hence wrong decision making. Establishing expectations is key but moving toward more optimal metrics also require resources and buy in from top management for overall success. This 5-day course is therefore intended to expose participants to the rudiments of data collection, metrics and analytics for strategic decision making.

Learning objectives:  At the end of the training, participants should be able to:

• Define Data
• Know the importance of data collection.
• Identify various sources of data collection.
• Identify various models for data analysis.
• How do predict outcomes resulting from my decisions
• How can I predict demand and allocate resources to ensure I am delivering services effectively?
• How can I find the patterns in vast amounts of data?
• Move from sense and respond to predict and act.
• How to transfer data into information and act on it
• Build a skilled data function with analytical data visualization and consulting skills.
• Develop an analysis road map for the range of analysis to be tracked and measured
• Establish data strategy that aligns, integrates data from multiple sources.
• Avoid garbage in garbage to ensure only clean data for optimal decision making.

For Whom.

Data analyst, statisticians, information managers, librarians, research officers, managing directors who wants to stay of top of their organization data metrics and analytics, head of HR, personnel of Government organizations handling Data etc.