{"id":6358,"date":"2021-03-02T15:51:43","date_gmt":"2021-03-02T18:51:43","guid":{"rendered":"https:\/\/patriciavasques.com\/?p=6358"},"modified":"2025-06-04T21:04:19","modified_gmt":"2025-06-05T00:04:19","slug":"modelta","status":"publish","type":"post","link":"https:\/\/qualiexpert.com.br\/en\/modelodelta\/","title":{"rendered":"Performance Indicator Analysis: DELTA model and 5 stages"},"content":{"rendered":"

Performance indicator analysis plays a fundamental role in business. While preparing the syllabus for the last event I conducted on Performance Indicators, I came across an article from Harvard Business School called \u201c3 examples of business analysis in action\u201d and I'd like to share it with you.<\/p>\r\n

From the article, I had access to the DELTA model and the 5 stages of organizational analytical maturity, which I didn't know and found very interesting! These 2 methodologies together provide support for diagnostic steps (AS-IS) , continuous improvement (TO-BE) and for making the organization oriented towards \u201cevidence-based decision making\u201d.<\/p>\r\n

(This month's newsletter is a free translation of the article \u201cDELTA Plus Model & Five Stages of Analytics Maturity<\/a>A Primer\u201d, written by Tom Davenport)<\/p>\r\n

DELTA model<\/strong><\/h4>\r\n

The DELTA model is an acronym and presents 5 elements that must be aligned for organizations to be successful during performance indicator and data analysis - to avoid weak or limited results.\u00a0<\/p>\r\n

    \r\n
  1. \r\n

    Data: Data must be clean, accessible, organized, unique, of high quality and integrated<\/p>\r\n<\/li>\r\n

  2. \r\n

    Entreprise-focus: Data analysis with a single, centralized and consistent perspective so that there are no duplicated efforts and tools, errors in analysis, inefficient use of resources, conflict between different groups and greater complexity of analysis between projects.<\/p>\r\n<\/li>\r\n

  3. \r\n

    Leaders: All levels of leadership embrace data analytics and drive the company's culture of data-driven decision making. In addition to the CEO or other top executive, all leadership should support data analysis<\/p>\r\n<\/li>\r\n

  4. \r\n

    Targets: Data analysis efforts must be aligned with specific strategic targets and corporate objectives<\/p>\r\n<\/li>\r\n

  5. \r\n

    Analysts: Talents for executing strategy in a complex and dynamic business environment. These professionals must have technical and interpersonal skills, business knowledge and the ability to train others<\/p>\r\n<\/li>\r\n<\/ol>\r\n

    Five stages of organizational analytical maturity<\/strong><\/h4>\r\n

    The maturity model helps companies measure their growth, strengths and weaknesses in the 5 elements mentioned above.<\/p>\r\n