Why implement Business Analytics in your Organization

Posted by | May 1, 2012 | Business Intelligence">

Top Five  Benefits of implementing Business analytics  in your organization.

• Business requires spontaneous and correct decisions, which is really impossible when you don’t have business analytics in place.   Business analytics helps organizations to derive better decisions which will yield best and improved results for the organization.

• Business analytics helps you circumvent business challenges. Business Analytics will help you exactly on how to escape from critical business problems.  Identify isses and opportunities at earliest stage allowing for either corrective action, interventions and or in the case of opportunities capitilizing on them as soon as possible.

• Business analytics helps you to know where your organization stands.  Actionable KPI’s presented through powerful Visualization tools will help to increase  performance, productivity and profits of the organization in the long run.

• You can increase the quality of your service/product over a period of time through Business analytics. It can really spot out the weaknesses of your organization and suggests where you need to strengthen it.

• Business analytics helps organizations achieve Better forecasting, high quality productivity and increased operational performance.

Business analytics will help you keep ahead of other competitors, take instant and correct decisions based on the past, help you to know about the weaknesses and strengths of the organization.

Business analytics exactly tells you where your organization is going wrong and suggest solutions for it. Business analytics is an absolute necessityin todays global and competitive world.

Replace spreadsheets as tools for business analytics. Spreadsheets are well established as a tool for analysis in organizations of all kinds and sizes, but they are ineffective for repetitive analyses shared by more than a few people. Yet research shows that along with business intelligence technologies (for querying, reporting and performing analysis) and analytic warehouses and databases, spreadsheets are the tools manufacturing companies most commonly use to generate analytics. Indeed, spreadsheets are used universally in 38 percent and regularly in more than half of these organizations. While they may be familiar, research shows that organizations using spreadsheets least have more accurate, timely data—and they deliver periodic reports about 40 percent sooner. Organizations should limit the use of spreadsheets as data stores and for repetitive analyses, particularly in cases where the results are reported to and used by more than a few people. Their failings, limitations and necessary work-arounds undermine the needs identified by participants to simplify analytics and metrics and ensure technology usability in the process of producing business analytics.

Don’t let inferior data undermine use of business analytics and metrics. Business analytics should be about determining what is happening and will happen to an organization. But the research shows almost seven in 10 manufacturing organizations spend the most time waiting for data, preparing data and reviewing it for quality and consistency. Conversely, only 28 percent spend most of their time on true analysis processes such as assembling scenarios, searching for causes and determining how changes will impact current business. If these preparation obstacles could be addressed, the amount of time people work with analytics could be reduced; currently, 60 percent are spending more than 25 percent of their time with them. Take steps to ensure your source data for analytics is both fresh and correct; if it isn’t, you risk undermining the use of metrics and KPIs as business improvement tools.

Understand the value of predictive and forward-looking analytics. Predictive analytics can give a business glimpses of what may happen, the consequences of actions and scenarios for how to respond to change. Technology has advanced to a stage where it is feasible to provide them to a variety of users in manufacturing businesses. Yet the research shows predictive analytics are not yet high-priority analyst capabilities for the lines of business (LOB) nor are what-if and planning-based analytics; each is deemed very important by less than 30 in the LOBs.

Business Analytics a need in todays competitive world where products and services are seen as commodities.

Business Analytics

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