Analytics becomes a decision discipline and innovation engine to pursue high performance in high mature intelligent enterprises.
Strategic analytics: Strategic management requires specialized knowledge of multifaceted analysis, and ideally, fresh insight to diagnose business problems and fix them smoothly. Nowadays, businesses are barraged with "data," information is refined data. Integrate big data into strategic decision analysis supporting corporate strategic decision and execution to achieve sustainable profit market shares. Analytics comes in stages to refine information into business foresight and customer insight. Analytics that doesn't help a business person make a decision is wasted data. Generally speaking, the good distinction between strategic vs. operational decisions are defined by time horizons. Analytics and optimization require an objective function to improve strategic decision-effectiveness.
Statistically, strategy has a very low success rate; thus, a focused emphasis on strategic objectives and ensuing strategic data analysis is a worthy pursuit. Strategic analysis involving multiple elements such as strategic design, vision, mission, values, KSF, strategic objectives, goals, plan, helps the management clarify cause-effect of business problems, pros and cons of decision-making; sequence and consequence of business actions. Strategic analysis helps to enhance standard and set strong disciplines for implementing strategic goals.
Systems analytics: Systems analysis is about understanding interrelationships between parts and the whole. Nowadays, businesses are open-ended systems that keep evolving, change is the new normal with increasing speed. Every system has a purpose. How many managers understand the difference between open and closed systems? How many business strategists understand Systems Thinking, concepts of emergence, requisite variety, relationships and boundary critique?
The executive team can leverage information-based analysis to understand what it needs to drive future business growth and improve cash flow. Information-based system analysis helps the management clarify business purposes. How to create business synergy by harnessing cross-boundary communication, integrating business processes and harmonizing organizational relationships. In order to solve problems systematically, look at the root cause, look at the context in which it has happened, and then expand into being a larger picture to solve larger problems, making it part of a whole wider world.
Risk analytics: You cannot manage risk, or for that matter, build a risk management capability without first understanding the "business value of risk management." Risk analytics tools help the management identify potential pitfalls, the root causes of business problems, the organizational risk assurance system robustness and maturity, etc, mitigate risks, improve organizational risk management effectiveness and intelligence.
One of the important aspects when designing a risk management process is to perform a risk analysis so all reasonable risks are avoided or eliminated at that precise moment. The value of risk management could be in better management decisions, improved operations, greater resilience, improved reputation, increased confidence in management, etc. Integrating risk management into the everyday business model helps to move the organization a couple of steps forward in improving business resilience and achieving business excellence.
Businesses that invest in analytics initiatives may cost a fortune in today’s competitive market, they need to see clearly tangible and intangible ROI in numbers. Valuation is based on financial metrics and projections for future revenues, cash flows, and income. Like any other engineering discipline, look for something in analytics initiatives, you could reuse before inventing from scratch; both in the need for a systemic view of a business (data science and analytics) and the difficulty in adopting new approaches. Analytics becomes a decision discipline and innovation engine to pursue high performance in high mature intelligent enterprises.
Statistically, strategy has a very low success rate; thus, a focused emphasis on strategic objectives and ensuing strategic data analysis is a worthy pursuit. Strategic analysis involving multiple elements such as strategic design, vision, mission, values, KSF, strategic objectives, goals, plan, helps the management clarify cause-effect of business problems, pros and cons of decision-making; sequence and consequence of business actions. Strategic analysis helps to enhance standard and set strong disciplines for implementing strategic goals.
Systems analytics: Systems analysis is about understanding interrelationships between parts and the whole. Nowadays, businesses are open-ended systems that keep evolving, change is the new normal with increasing speed. Every system has a purpose. How many managers understand the difference between open and closed systems? How many business strategists understand Systems Thinking, concepts of emergence, requisite variety, relationships and boundary critique?
The executive team can leverage information-based analysis to understand what it needs to drive future business growth and improve cash flow. Information-based system analysis helps the management clarify business purposes. How to create business synergy by harnessing cross-boundary communication, integrating business processes and harmonizing organizational relationships. In order to solve problems systematically, look at the root cause, look at the context in which it has happened, and then expand into being a larger picture to solve larger problems, making it part of a whole wider world.
One of the important aspects when designing a risk management process is to perform a risk analysis so all reasonable risks are avoided or eliminated at that precise moment. The value of risk management could be in better management decisions, improved operations, greater resilience, improved reputation, increased confidence in management, etc. Integrating risk management into the everyday business model helps to move the organization a couple of steps forward in improving business resilience and achieving business excellence.
Businesses that invest in analytics initiatives may cost a fortune in today’s competitive market, they need to see clearly tangible and intangible ROI in numbers. Valuation is based on financial metrics and projections for future revenues, cash flows, and income. Like any other engineering discipline, look for something in analytics initiatives, you could reuse before inventing from scratch; both in the need for a systemic view of a business (data science and analytics) and the difficulty in adopting new approaches. Analytics becomes a decision discipline and innovation engine to pursue high performance in high mature intelligent enterprises.
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