Do Multipliers Trump Big Data Analytics?

by Chris Pehura – C-SUITE DATA

DO MULTIPLIERS TRUMP Big Data analytics?

A multiplier is a factor used to estimate the impact an input has to the total end-result. Multipliers are useful tools for understanding, planning, and forecasting. They are used in risk management, business planning, and business development; specifically returns on investment, productivity, cash flow, and revenue growth. Analytics, on the other hand, are automated analyses on data and statistics.

Analytics are used as inputs to our decision-making and just like multipliers, analytics are useful for understanding, planning, and forecasting. Because of their similarity, multipliers and Big Data analytics are tightly integrated. Multipliers feed into and improve the accuracy of our analytics. Analytics feed into and improve the accuracy of our multipliers.

Because of their tight integration multipliers and analytics should be used together at all levels of the organization. The challenge is that their use changes based on the level they’re applied.

Multipliers drive executive leadership and strategies.

Big Data analytics streamline and align those strategies. Multipliers are our common business language and business planning tools for us at the executive level. They allow us to develop our principles, vision, and mission. They help us understand what is important for our organization and what to say to communicate that importance. Multipliers give us a broad understanding of our organization, our business models, and our Big Data.

“Based on our multipliers how should our culture, our organizational structure, or our cash flow drive our decision making?”

“Should culture trump strategy and our executive leadership’s expertise?”

“What kind of executive is best for our organization?”

Our multipliers make it clear what we should do. Analytics make it clear on the course we must take to get it done.

Big Data analytics drive daily and monthly operations.

Multipliers streamline and align those operations. Analytics are our common language used within a narrow silo of our organization. They allow us to be more proactive so we satisfy our customers’ needs and the demand of our operational activities. Analytics also allow us to estimate our short-term plans and help us troubleshoot our deep-rooted issues. They give us our deeply narrow understanding of how to streamline our multipliers and our Big Data solutions.

“Which customers and activities are the most important?”

“How does this impact our strategies?”

“How does this impact our executives’ business planning?”

Our analytics help us deeply understand a silo of our organization. Our multipliers help us connect silos together to build a much broader understanding.

Multipliers and Big Data analytics are consolidated by corporate governance, data governance, and at times IT governance.

Governance is the best place to consolidate and balance our multipliers with our analytics. Governance provides a forum where we can do our due diligence both politically and procedurally. By emphasizing our integration of our multipliers and analytics we have a clear path on how to use Big Data across our organization from business planning, to business development, to operations, to risk management. By focusing on integration we stay on track through fire drills, flavors of the month, and political waves. We also craft an accurate big picture where we can strategically distribute our multipliers and analytics across our organization so we better understand, manage, and lead our organizational structure, culture, cash flow, and Big Data solutions.

“How do our producers, organizational structure, and managers impact each other?”

“How can we get the best of our managers and leaders with our culture, behaviors, and habits?”

“How does our culture and brands impact our customers, suppliers, and cash flow?”

Using governance to integrate and balance our multipliers and analytics keeps us focus on the decisions we need to make and the actions we need to take.

Multipliers and Big Data analytics are tightly integrated. By focusing on how they integrate and how they balance we better forecast the impacts of our investments with the better use of our Big Data.

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