The Right Way to Analytical Success

Mon, 01/21/2013 - 06:40 -- admin

In order to make success in analytics, both strong analytical leaders and executives who are willing to make a long-term commitment are needed. Nowadays, the analytical leaders spend as much time discussing how to manage people, projects, and processes as they do technology and architectures.

Analytics is not a one-time project. It's a program which requires a long-term investment. We are talking about investment of money, time and expertise. It requires a lot. From treating data as a corporate asset to changing the point of view and manage data, in order to make good decisions.

So, this basically means that in order to succeed with analytics, companies must have the right architecture, people, culture, organization and process. And this is not such a simple task to do. It requires a lot of work. That’s why the most of the analytical leaders spend much more time discussing selling, marketing, and teamwork as they spend talking about technology and tools. It's just necessary.

Some of the most important areas, which are required to run a successful analytics program, are listed below.

The Right Architecture

Every analytical organization needs tools and technologies to do its work. It extends existing data warehousing environments with new database processing platforms and complements top-down monitoring with bottom-up ad hoc exploration. It also provides the right tools to the right people so they can generate or consume data-driven insights. Finally, it implements agile processes that accelerate software development while maintaining data consistency and models across business units—a sizable challenge that few organizations have yet to master.

The Right People.

It’s impossible to do analytics without good data developers and analysts. Data developers build and maintain the data structures (e.g., data warehouse, master data management, BI semantic layers) and create complex reports and dashboards. Analysts, on the other hand, explore the data and generate reports and dashboards to answer ad hoc questions asked by the business. Both data developers and analysts require a passion for data, along with a blend of people skills, technical expertise, and business knowledge. It's not so easy to hire such a people.

The Right Culture

Culture refers to the rules—both written and unwritten—for how things get done in an organization. These rules emanate primarily from the words and actions of top executives. Business executives must have a vision for analytics and the willingness to invest in the people, processes, and technologies for the long haul to ensure a successful outcome. Technical executives must be able to talk the language of business and recruit business people to work on their teams. They also need to manage all components of the analytics program, from data warehousing to business intelligence to advanced analytics.

The Right Organization

Every company needs to cultivate a federated organizational model to succeed with analytics. Centrally, it needs a center of excellence that establishes and inculcates best practices for building analytical applications and provides a forum for team members to share ideas and techniques. Departmentally, it needs embedded data developers who can quickly build data-driven solutions as well as embedded analysts who can quickly address ad hoc questions. Sometimes, these are one and the same person, but not always. In addition, a federated organization needs to manage shared data as an enterprise resource while empowering departments to build their own reports, dashboards, and analytical models. This dual focus requires some tricky organizational choreography that most companies have yet to master.

The Right Process

A hallmark of an outstanding analytical program is that it has standard processes and procedures for doing things, such as managing projects, developing software, gathering requirements, communicating across business functions, deploying analytical models, handling job errors, designing and changing data models, evaluating and selecting new tools and technologies, and ingesting external data, among other things. However, analytical managers must be careful not to overburden their teams with too many processes and standards that impede agility and undermine flexibility.

After all, we get to the summary and realize that there are many factors involved in running a successful analytics program. But providing the right architecture, people, culture, organization and process are the basis for success. 





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