Role of CIO in driving enterprise analytics

The role of a CIO (Chief Information Officer) is very prominent in this current scenario of increased rise in need for management of advancing resources of IT. He/she is the one who’s responsible for establishing a better business/IT alignment with in an organization. But recently the role has greatly changed from just responsible for the tasks related to IT or Information Technology, rather CIOs need to make sure there is better alignment in enterprise analytics. So what kind of jobs do they perform in an enterprise to drive and boost the organizational goals?

role of CIO

The very first task of a CIO is to perform the role of a leader, i.e. a business leader. But In this fast pace digital world, he must play a dual role: builder of technology and builder of business. The digital technologies are putting pressure on IT organizations and CIOs have to manage it through strategy innovation and revenue growth by building and integrating a cost-effective information system.  Being an officer of the senior most rank, a CIO shall make decisions regarding purchase of equipment’s related to IT departments also they are solely responsible for handling and managing the tasks of his executives. But the changing technological market aspire leading CIOs to take a more expansive view of their role. No longer is their job merely to build and operate the technology their business needs to function. Since IT is part owner of the company’s analytical capabilities, IT managers must understand and be able to articulate the potential for analytics being created at an enterprise level. IT organizations should, also, build an IT infrastructure capable of delivering the information and analytics that people across the enterprise need not just now but also in the future. Increasingly, they see their role as helping to increase revenue, improve customer experience, and coax insight out of the growing amount of data generated by company’s digital operation and shape strategy. Because of this reason CIOs have to keep an eye on the mechanism of data delivery and data management and data analytics. Data analytics is a place where the CIO can drive better business and IT alignment. Getting at the right analytical questions serves as a forcing function for better system design and for ensuring that systems better meet business objectives.

Organizations should have an enterprise analytics strategy. The analytics strategy should be about how do you answer business critical questions. This strategy needs to be determined and shaped by business strategy. Business strategy needs to determine what data is needed and what analytics are needed to present this data. This includes advanced analytics. As an IT leader, CIOs probably get pulled into departmental projects and receive requests for new analytics solutions all the time. He can come up with a successful enterprise analytics that include essential components like

  • Get the right data together and manage it efficiently.
  • Make data accessible so people can play with it freely and innovate.
  • Identify analytics tools and structures for the enterprise.
  • Create a culture of analytics that’s built on reproducible processes.
  • Measure how analytics is changing your business

Once an efficient enterprise analytics strategy is in place CIOs can lead their team to adopt analytics-driven planning and decision making.

Are you ready to develop an enterprise strategy that helps your organization fully leverage analytics? For example, what if you could transform data in ways that tell key business decision makers something that they don’t already know? This would, for example, empower executives to make more strategic business decisions by enabling them to simulate the future consequences of different choices and scenarios and make the choice that will result in the best improvements in KPIs. The opportunities and potential for business impact are huge – so what are you waiting for? Talk to us


Cloud Analytics for business success

Fueled by the growth of big data tools and the proliferation of valuable data sources, enterprises are concentrating more towards scalable cloud infrastructure to analyze data rapidly, often real-time. Cloud computing has already changed the business model for many organizations and is now forcing them to rethink on the effective use of analytics to gain competitive advantage in an organization.

cloud analytics

Cloud often regarded as a cost effective approach to improved efficiency while maintaining the necessary controls has now effectively involved in helping organizations advance in their analytic sophistication. Organizations can use the combination of cloud and analytics to capitalize on their emerging trends, which in turn can reduce costs, increase profitability and open new markets. Analytics over cloud enables organizations to realize their analytical needs in a more affordable way.

Analytics have largely evolved from a business initiative to a business imperative. A few decades back, there was a shortage in information or data. But recently as we enter the era of Big Data, a heap of data, both unstructured and structured are available for analysis. Gaining actionable insight from all this data is a business necessity. But the major challenge is how to analyze this data. Processing the rapidly generating data in the current infrastructure is a major challenge. Though huge and dedicated servers were developed to solve this problem, the costing factor remains a major concern. But today the explosion of cloud computing has made it feasible. A data warehouse for enterprise data that is made available to users from a remote location operated by the service provider, rather than being located on the enterprise’s own systems.

Cloud analytics refers to applications that use cloud resources for analytics processing or the delivery of analytical insights. Unlike the usual analytics, the analytics on cloud require separate functionality to leverage the cloud infrastructure for complex tasks. Business should follow an iterative and disciplined approach while using analytics to drive better outcomes. Organizations need to be perfectly aligned in order to meet the objectives. Once aligned properly, organizations need to determine the right capabilities to anticipate, predict and shape business outcomes. As a last step business need to embed analytics into their core process to optimize outcomes.

Cloud analytics applications and services are typically offered under a subscription-based or utility (pay-per-use) pricing model. Two kinds of services namely, Analytics as a Service (AaaS) and Model as a Service (MaaS) can be visualized for cloud analytics. In AaaS customers can pick the required analytics solution and leverage it for the specific purposes and pay for the usage. AaaS will be highly cost-effective as the data is publicly available on web blogs or review articles. In MaaS users can subscribe to various building block models available in the cloud to develop their analytical solutions.

Cloud based analytics can often help the business in different ways. Analytics can typically use to identify the potential customers, analyze trends, transform the planning process with rolling forecasts and the ability to rapidly adjust and realign resources, Identify quality issues early, ensure financial controls integrity and determine the next best action.

Recent studies reveal businesses using analytics extensively via cloud to derive insights for better business decisions are likely to generate double revenue and profit compared to their peers. Utilizing the benefits of cloud computing could be a way for more organizations to broaden adoption rates and reap the benefits that analytics can provide.

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