To get the success of business intelligence is not just a powerful technology platform. It requires a very subtle focus on processes and people, and gains insights from the data in a business-first manner.
Business intelligence (BI) is critical to business growth and competitive advantage, but the benefits of business intelligence cannot be achieved by technology that can achieve it.
Boris Evelson, vice president and principal analyst at Forrester Research, said that the simplest part of a business intelligence initiative is the deployment of technology. He said that dealing with the people and the parts of the process is more challenging.
Therefore, if an organization is to succeed, people and processes must be key aspects of its business intelligence strategy. In addition, business intelligence strategies should be further subdivided to address both ownership and continuous improvement issues.
Several business intelligence experts believe that the following are the seven elements of a successful business intelligence strategy.
1. Granting Business Intelligence Ownership to Business
Evelson says organizations that give business intelligence to users are more organized than organizations that limit business intelligence to IT. High success rate. He said this could mean embedding business intelligence in the industry or reporting business intelligence operations to chief digital officers or chief customer officers.
He added: “Business must be absolutely responsible.”
Although the complexity of early business intelligence technology made IT responsible for many business intelligence programs, the tools are now more intuitive. It can be used directly by business users, and business users can use these tools to run queries that are important to them.
Similarly, the speed at which users need to access data and the insights gained from business intelligence have increased dramatically in recent years. Today’s business users often need real-time operational information, and can’t wait for IT to generate reports.
Evelson said that, therefore, ownership of IT may hinder rather than drive the success of business intelligence.
2. Monitor business intelligence and make adjustments when necessary
Although business should have a business intelligence plan, IT must monitor and evaluate business intelligence The use of the system continues to be an active partner.
Evelson explained: “It’s better to monitor what they are doing, what data sources they are accessing, what tools they are using, and how to use them, and whether the use of business intelligence by a business unit is More than B business unit.”
He said that in this case, the CIO can set a threshold with the business unit. For example, the CIO will know if some of the analysts in marketing have downloaded their tools and successfully used it, in which case it might be a good thing not to intervene. Similarly, CIOs will notice when business intelligence applications are witnessing an increasing number of users across the business, becoming enterprise-class environments and mission-critical enterprise applications that require additional discipline and governance.
3. Validation, verification, verification
Chris Hagans, vice president of business at WCI Consulting, a business intelligence consulting firm, says organizations may want to be fast Create a lot of business intelligence features, but quality is better than quantity.
He said: “It’s better to have a few things that are trustworthy than to have a lot of doubts.”
Therefore, the organization needs a strong verification process. The process focuses on accessing all the data that needs to be answered. It should also prevent problematic data from entering the business intelligence system so that it does not produce flawed insights. In addition, the verification process should be sensitive enough to respond quickly to requests for new BI functions.
Hagans pointed out a hypothetical use case in which business intelligence tools generate reports on net sales. If the tool receives sales data but does not take into account the quantity of goods returned, the final information is of little value.
Hagans said: In addition, verification is not only important to ensure accuracy, but also to block skeptics.
He said: “As long as one or two people say ‘I don’t trust the data’, the report will be invalidated. This completely defeats the entire project and the report becomes worthless.”
4. Focus on business issues first, then focus on the data
Evelson warns against taking a “must have a way to get to the mountain” approach to the BI program. He said that too many organizations build data repositories, put business intelligence at the top, and expect business users to get started.
He said: “In terms of business outcomes, the top-down approach works better. We don’t start with ‘where the data is,’ but start with solving business problems.”
Evelson explains this example: Marketing finds customer churn and wants to know why customers are leaving. Organizations should focus on providing the ability to answer marketing business questions, first determining which metrics to measure, accessing the data needed to calculate those metrics, and then enabling marketing to slice and diced the data.
Evelson said: “We first need to identify a clear business problem, and which metrics we want to analyze, and then finally discuss where the data is obtained.”
5. Prioritize and build improvement processes
According to business intelligence leaders, successful business intelligence strategies are expected to expand and improve.
Therefore, organizations should know what business insights they want and which ones are most important, so IT can first provide the most critical things for business users and implement them through a prioritized list.
In addition, business intelligence initiatives should be able to change as priorities change.
Hagans said: “It must evolve with the needs of users and people in the business community.”
Also, business intelligence strategies should be built on the process of improving and improving the way the system works. Evelson recommends an iterative approach so that business intelligence tools can scale and improve as the business unit uses it, and determine where it meets its needs and where it can’t.
6. Improve 'Citizen' Skills of Data Scientists
Research company Gartner’s “Business Intelligence and Analytics Platform” in 2017 The Magic Quadrant reports that “the number of citizen data scientists will grow five times faster than data scientists in the next few years.”
Ginner’s vice president of research, Cindi Howson, said executives have recognized that data scientists’ deficiencies are difficult to meet; they are also trying to hire or discover the citizen data scientists they need from existing members. .
She said: “We are talking about information analysts during their stay. They understand the business area and the questions to ask, she added, people need software that is easier to use so that the organization can better support it. These staff.
Howson predicts that software improvements will eventually allow merchants to ask and answer their own questions on unmodeled data sets. Once this happens, the organization needs the right people to act. The role of citizen data scientists. They need curious staff with analytical skills and questions, they know how to read the information back, and are happy to use software to improve business outcomes.
7. Granting employees the right to tell stories with data
CBIG Consulting is a professional services company that helps clients leverage data assets, says Todd Nash, president and head of the company. In a case where he worked with organizations that understand how to use the insights provided by business intelligence tools to help others understand that “data is trying to express “The story,.
He said that these people use the reporting and visualization features built into business intelligence technology to develop narratives that help maximize the value of analytics.
He said “You have the data and tools to tell the story, you need someone to be with it.”
This is not just for people to generate glamorous reports; Nash says that these users can Data that others can’t see makes connections, providing new insights that companies can make a profit.
He said that when these workers explore these relationships and show their insights, executives need Provide support and give them the right to do so.
For example, he said, employees who analyze store sales data may see subtle effects of subtle weather trends (not just big storms) on sales. You may want to introduce external weather data to further analyze trends and better understand how stores can optimize sales through new insights.
Nash says: “You can use a variety of internal and external data to get better. Insight.” He added success Business Intelligence program allows analysts to do more than just measure key performance indicators so simple
He said:. “Challenges There are many ways of self. Part of it is the challenge of each key performance indicator and ensuring that you have access to information to understand.
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