Intelligence-led Performance Management is a holistic management discipline that needs to connect many relevant dots related to business development, enablement, enhancement, and apply predictive or prescriptive analytics to improve its effectiveness.
In practice, business intelligence-led performance management with the following characteristics will bring business leaders together across the organization to share data-based insight wherever there is a gap in the system, to provide practical guidance for improving business performance ultimately.
Comprehension: Corporate performance Management is a management control across functional domains and management disciplines. Business Intelligence-led performance management implies the ability to make inferences or predictions from the performance data for making continuous business performance improvement. Organizations can harness the power of data to provide the business with a more fact-based performance oversight through identifying the right data, validating it and communicating it to the right people at the right time for making continuous improvement.
In reality, some traditional performance management practices cause silo mentality, dysfunctional behaviors, and even motivate people to hide bad news on delays and cost overruns. It's critical for the company to share comprehensive information among its primary stakeholders, to make business intelligence-driven performance management more “visible” for them. Well-defined performance indicators have functional specifications detailing its meaning, intent, relationships to other measures, calculation, data requirements, reporting requirements and ownership. Not all business value is directly related to ROI. Business intelligence-led performance management expands the concept of the value of the firm beyond economic value or shareholder value, to include other forms of value such as employee value, customer value, supplier value, channel partner value, alliance partner value, managerial value, and societal value, etc.
Rationalization: Today’s digital business environment is dynamic, complex, and uncertain. There are always different complexities at a different time or dimension, Performance Management is all about managing performance by that data and dealing with the overall performance of a company which relies on a few KPIs, reflecting the good or poor execution of a strategy. Business intelligence-led performance management can leverage data-based analytics to rationalize performance results and improve business-value creation and measurement cohesively.
It's fair to say any organization that didn't have a systematic approach to measurement and performance analysis at both the strategic level and operational level has a giant blind spot that is impairing their performance. Business Intelligence led Performance Management aims in improving an organization’s performance with logical cause-effect analysis and tangible results of performance improvement. The measurement and timely communication of performance will assist in the achievement of a unit/organizational goals. As such, the intelligent process of defining and the creation of personal and unit objectives must be constructed within the goals and objectives of the company.
Triangulation: Due to the complexity and volatility of modern organizations, it is very hard to measure holistic organizational performance objectively and meaningfully. The struggle for performance measurement or key performance indicator selection is that they sometimes need a number of measures around the same issue to gain a complete picture. So organizations leverage triangulation - use varying sources, measures, and methods of collection/analysis for various assessments. With reliable performance data, the management can guide the team to understand the purpose of doing metrics and engage in that, and fix the root causes of the problem radically.
Conduct a comprehensive performance assessment; not just data exploration, but thorough getting feedback through different sources, or using different tools, etc. Selection of the right set of performance indicators is more critical than measuring them right. The proper set of performance metrics will help to present the tangible results via actions taken, and also make it possible to improve the future performance. Spend the time upfront organizing and unifying the data you collect across systems and services, so you can build common performance analytics tools that allow you to spend their time investigating data-based performance results. Triangulation is helpful. However, keep in mind, companies have resource constraints, and that performance management, per definition, is “overhead.” This would imply that there exists a trade-off between the realization of value through formalizing and structuring performance management processes and practices and the attached costs.
Contextualization: There are both strategic levels of performance and operational level of performance. How well the performance management objectives are directly tied to the achievement of the company's overall business objectives and strategic plan goals. The management needs to assess performance measurement and management contextualization and effectiveness by asking: Do the indicators, when put together, tell the complete story? Do they fully answer your WHY? Use metrics as pointers to areas requiring further investigation. Intelligence-led performance management helps to understand performance data, discover the patterns in them, and derive value for the business betterment.
Performance Management is contextual. Wrong selection of key performance settings could have the devastating effect on the business. Performance Indicator definition needs two things: High impact and high information context. The high impact is the predictive power, with a high impact on the performance results you're trying to understand or control. KPIs with high information content and context tend to be specific to a strategy and speculative, so you must test them to be sure they have the impact on results you think you have. From a long term perspective, if you want to manage measurements effectively, you need to understand what those metrics are at the different levels of the organization, what they are trying to achieve, and why you think it is appropriate in that specific context. Otherwise, it causes confusion and resistance in using metrics when people aren't clear about what information they want to collect and how they intend to use the information to support decisions for continuous improvements.
Optimization: Most organizations fail to look into the system holistically and manage performance effectively. Therefore, if you want an effective performance evaluation or management, data-based analytics needs to be embedded into key processes, enabling the business management to refine and optimize performance indicators, processes and systems in a structural manner. Future performance is a focal point. It’s critical to combine Business Intelligence and corporate performance management with workflows for advanced budgeting and prognosis processing as well as dynamic planning, managing ongoing Performance Management to deliver better results.
To unlock business performance, what is getting more attention is the improvement of the "intelligence" and "effectiveness" of the holistic performance system. Intelligence-enabled processes in a systematic manner focus on optimizing future performance and keep the end - business goals in mind. Predictive analytics might be what is seen through the windshield. The purpose of all such management disciplines and practices is to ensure enterprise vehicles run at optimal speed in the right direction.
You can only manage what you measure. Intelligence-led Performance Management is a holistic management discipline that needs to connect many relevant dots related to business development, enablement, and enhancement, and apply predictive or prescriptive analytics to improve its effectiveness and take a holistic performance management solution that adds value to employees, organizational goals, and business results consistently.
Comprehension: Corporate performance Management is a management control across functional domains and management disciplines. Business Intelligence-led performance management implies the ability to make inferences or predictions from the performance data for making continuous business performance improvement. Organizations can harness the power of data to provide the business with a more fact-based performance oversight through identifying the right data, validating it and communicating it to the right people at the right time for making continuous improvement.
In reality, some traditional performance management practices cause silo mentality, dysfunctional behaviors, and even motivate people to hide bad news on delays and cost overruns. It's critical for the company to share comprehensive information among its primary stakeholders, to make business intelligence-driven performance management more “visible” for them. Well-defined performance indicators have functional specifications detailing its meaning, intent, relationships to other measures, calculation, data requirements, reporting requirements and ownership. Not all business value is directly related to ROI. Business intelligence-led performance management expands the concept of the value of the firm beyond economic value or shareholder value, to include other forms of value such as employee value, customer value, supplier value, channel partner value, alliance partner value, managerial value, and societal value, etc.
Rationalization: Today’s digital business environment is dynamic, complex, and uncertain. There are always different complexities at a different time or dimension, Performance Management is all about managing performance by that data and dealing with the overall performance of a company which relies on a few KPIs, reflecting the good or poor execution of a strategy. Business intelligence-led performance management can leverage data-based analytics to rationalize performance results and improve business-value creation and measurement cohesively.
It's fair to say any organization that didn't have a systematic approach to measurement and performance analysis at both the strategic level and operational level has a giant blind spot that is impairing their performance. Business Intelligence led Performance Management aims in improving an organization’s performance with logical cause-effect analysis and tangible results of performance improvement. The measurement and timely communication of performance will assist in the achievement of a unit/organizational goals. As such, the intelligent process of defining and the creation of personal and unit objectives must be constructed within the goals and objectives of the company.
Triangulation: Due to the complexity and volatility of modern organizations, it is very hard to measure holistic organizational performance objectively and meaningfully. The struggle for performance measurement or key performance indicator selection is that they sometimes need a number of measures around the same issue to gain a complete picture. So organizations leverage triangulation - use varying sources, measures, and methods of collection/analysis for various assessments. With reliable performance data, the management can guide the team to understand the purpose of doing metrics and engage in that, and fix the root causes of the problem radically.
Conduct a comprehensive performance assessment; not just data exploration, but thorough getting feedback through different sources, or using different tools, etc. Selection of the right set of performance indicators is more critical than measuring them right. The proper set of performance metrics will help to present the tangible results via actions taken, and also make it possible to improve the future performance. Spend the time upfront organizing and unifying the data you collect across systems and services, so you can build common performance analytics tools that allow you to spend their time investigating data-based performance results. Triangulation is helpful. However, keep in mind, companies have resource constraints, and that performance management, per definition, is “overhead.” This would imply that there exists a trade-off between the realization of value through formalizing and structuring performance management processes and practices and the attached costs.
Contextualization: There are both strategic levels of performance and operational level of performance. How well the performance management objectives are directly tied to the achievement of the company's overall business objectives and strategic plan goals. The management needs to assess performance measurement and management contextualization and effectiveness by asking: Do the indicators, when put together, tell the complete story? Do they fully answer your WHY? Use metrics as pointers to areas requiring further investigation. Intelligence-led performance management helps to understand performance data, discover the patterns in them, and derive value for the business betterment.
Performance Management is contextual. Wrong selection of key performance settings could have the devastating effect on the business. Performance Indicator definition needs two things: High impact and high information context. The high impact is the predictive power, with a high impact on the performance results you're trying to understand or control. KPIs with high information content and context tend to be specific to a strategy and speculative, so you must test them to be sure they have the impact on results you think you have. From a long term perspective, if you want to manage measurements effectively, you need to understand what those metrics are at the different levels of the organization, what they are trying to achieve, and why you think it is appropriate in that specific context. Otherwise, it causes confusion and resistance in using metrics when people aren't clear about what information they want to collect and how they intend to use the information to support decisions for continuous improvements.
Optimization: Most organizations fail to look into the system holistically and manage performance effectively. Therefore, if you want an effective performance evaluation or management, data-based analytics needs to be embedded into key processes, enabling the business management to refine and optimize performance indicators, processes and systems in a structural manner. Future performance is a focal point. It’s critical to combine Business Intelligence and corporate performance management with workflows for advanced budgeting and prognosis processing as well as dynamic planning, managing ongoing Performance Management to deliver better results.
To unlock business performance, what is getting more attention is the improvement of the "intelligence" and "effectiveness" of the holistic performance system. Intelligence-enabled processes in a systematic manner focus on optimizing future performance and keep the end - business goals in mind. Predictive analytics might be what is seen through the windshield. The purpose of all such management disciplines and practices is to ensure enterprise vehicles run at optimal speed in the right direction.
You can only manage what you measure. Intelligence-led Performance Management is a holistic management discipline that needs to connect many relevant dots related to business development, enablement, and enhancement, and apply predictive or prescriptive analytics to improve its effectiveness and take a holistic performance management solution that adds value to employees, organizational goals, and business results consistently.
0 comments:
Post a Comment