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Critical Decision Making

Leverage Data for Critical Decision-Making

Let’s examine real-time, near-real-time, or batch-based data scenarios in more detail, including the people, processes, and system changes you must consider.
1. Emergency Call Centers: Real-Time Data for Life-Saving Decisions
Having up-to-date information is crucial for operators in emergency call centres. Lives depend on the accuracy and timeliness of their data.

You’ll need:
• Source systems that allow streaming of real-time data or that can batch information in near-real time (i.e. such as the location of emergency vehicles or resources every 30 seconds)

• A system with large processing and storage capacity, along with a policy on how much data to keep over the long term – the volume of data cannot be understated here

• Tools that allow you to display real-time streaming data. If the data is coming in via a stream, the last thing you want to do is force a batch process to consume the data, increasing time from data input to decision-making.

• Machine Learning algorithms that can consume vast data and help identify gaps in real-time decision-making.

In return, you’ll get:

Real-Time Data Integration: By aggregating and displaying real-time data from various sources, operators can make informed decisions swiftly.

Interactive Dashboards: Customizable dashboards provide a comprehensive view of ongoing situations, enabling quick response times.

Predictive Analytics: Leveraging machine learning models, operators can anticipate potential issues and respond proactively.

2. Business Cash Flow Management: Navigating Financial Health
Managing cash flow effectively is vital for any business. It's essential to have a clear picture of both current and future financial activities.

You’ll need:
• Defined guidelines and processes that capture and measure expenditure in the business including purchase requisitions & credit cards.

• Up to date accounting processes where month end is being closed quickly (in days not weeks or months)

• Well kept accounts payable and receivable records

• Known scenarios from management on how cash might need to be allocated from a strategic initiative perspective.

• Agreed accounting principles across the business for all entities including a standardised chart of accounts

In return, you’ll get:

Detailed Financial Reporting: Create detailed reports that include current and projected cash flows.

Scenario Analysis: Model different spending and revenue scenarios to plan for various outcomes.

Automated Alerts: Set up alerts for any anomalies in cash flow patterns, ensuring timely interventions.
3. Strategic Initiatives: Informed Long-Term Planning
When it comes to long-term strategic decisions, having data that is as recent as today is beneficial, but often, not essential.

You’ll need:
• A single strong strategic vision

• Research on the current market including customer behaviour and competitors

• Standardised metrics to measure the business and outcomes of strategic objectives

• A consolidated data repository, such as a Lakehouse, to collect data from many different sources and business functions

In return, you’ll get:

Historical Data Analysis: Access and analyze historical data to identify trends and inform future strategies.

Single source of truth: A single lens for the entire organisation.

Data-driven decisions making: Reduced silos and improved confidence in decisions making capabilities.
Conclusion
You need to think about how data aligns with the strategic objectives so that it can empower and lead your organization to make data-driven decisions.

Whether you are dealing with life-critical situations, managing business finances, or planning long-term strategies, by utilising data, companies can ensure they have the right information at the right time to make impactful decisions.