Innovative organizations are using data as an asset to drive market differentiation and growth. Business success nowadays depends on Data and Analytics (D&A) capabilities that can scale with business ambitions.
According to Gartner, organizations need to improve the flow of value to customers and establish a clear connection between D&A and business value creation. To be successful in these initiatives, organizations need to develop business decision-making processes and the underlying D&A ecosystem enabling decisions.
Many organizations need help to build or improve D&A capabilities that add greater business value. According to a Global Survey done last year by McKinsey. Most executives expect their analytics activities to positively impact on company revenues, margins, and organizational efficiency in the coming years. To date, respondents report mixed success in meeting their analytics objectives. A lack of strategy or tools is not necessarily to blame for those lagging. Instead, the results suggest that the biggest hurdles to an effective analytics program are a lack of leadership support and communication, ill-fitting organizational structures, and trouble finding (and retaining) the right people for the job.
Companies need to evolve with their data to implement a D&A program that can eventually help them succeed in providing on-time business insights and AI enablement.
Following is a quick startup guide for driving the D&A program with impactful business outcomes.
Step 1: Strategy & Planning
- Prioritize – Key business areas to analyze and improve
- Determine – The initial business questions to investigate
- Educate – Stakeholders about the benefits of business analysis
- Plan – Define success, create timelines and outcomes
- Build – Internal Support
Step 2: Establish and Collect
- Inventory – Data sources and decide how much to include
- Establish – A Master Data Management Policy
- Create – A dictionary that defines standard business terms
- Combine – & integrate critical data sources in a central data mart
Step 3: Clean & Standardize
- Define – Acceptable standards for data cleanliness
- Correct – Duplicate, missing, and inconsistent data
- Standardize – Procedures to reduce future data discrepancies
Step 4: Build and Analyze
- Tech – “Data-Driven Decision-Making Mindset” to shift the culture
- Visualize – Data with interactive dashboards
- Forecast – Outcomes with predictive analytics
- Discover – Patterns and correlations through data mining
- Ask – New questions with data discovery
- Iterate – Through the process to refine
Step 5: Communicate and Educate
- Demonstrate – Results to communicate value
- Ensure – The level of detail is appropriate for the audience
- Describe – The visualizations with stories
- Encourage – Questions and new hypotheses
- Tech – Right tools to speed adaption
- Share – Success and show value
An approach can be devised to address the organization’s immediate and long-term D&A needs for building or improving these capabilities. A D&A assessment can show where the most focus is needed in the above steps to accelerate the D&A program for immediate results.
We have assisted dozens of organizations in their D&A optimization and alignment journey, including prominent organizations in healthcare, associations, nonprofits, education, manufacturing, logistics, and supply chains. For more information and guidance, you can reach us at email@example.com.