BI (Business Intelligence) is a roadmap to the business success.
Wikipedia: “Business intelligence (BI) is a set of theories, methodologies, processes, architectures, and technologies that transform raw data into meaningful and useful information for business purposes. BI can handle large amounts of information to help identify and develop new opportunities. Making use of new opportunities and implementing an effective strategy can provide a competitive market advantage and long-term stability.”
BI tools access and analyze data sets and present analytical findings in reports, summaries, dashboards, graphs, charts and maps to provide users with detailed intelligence about the state of the business.
The term business intelligence often also refers to a range of tools and technology that provide quick, easy-to-digest access to insights about an organization’s current state, based on available data.
how do I know when to use business intelligence for my business?
In another words, which business problems BI can solve?
For far too many organizations, business intelligence (BI) brings to mind simple statistical summaries in stodgy, dated reports.
But beneath BI’s dull surface, keen insights await — especially for those willing to revamp their business intelligence strategy to tackle the kinds of issues forward-thinking organizations are already addressing with modern BI.
If your company is struggling with any of below reason, you need a BI solution in place with the right BI Strategy:
1. Integrate and Analyse the data from different data sources
Reporting/analysing across multiple systems or data sources is the biggest challenge. Data may be stored in various ERP systems, CRMs, databases and Excel spreadsheets – across multiple systems, getting the information you need can be an arduous task.
2. Access to the Data is limited
Organizations have loads of data to analyse residing on multiple systems’ data sets. How to access, analyse and share it with the concern stack holders.
3. Poor Performance Management
You have a great product or service, your visionary approach is making a difference, but how is your business doing now or over a two-year period?
Business do not have insight to understand and analyse business performance and opportunities on a deeper level. In absence of meaningful analysis and reporting, business can’t make well-informed and insightful, long-term strategic and tactical decisions quickly and efficiently.
4. Slow Market Response
One of the biggest problem for the business is, to look into what the market is purchasing now. Management has to view reports at the end of the month or quarter, unable business to respond quickly to unpredictable situations and market demands. Real time, on demand insights are vital for the business.
5. Losing Customers
Traditional reporting does not show the detailed customer behaviour insights by certain metrics and analyses: interests, preferences, history, demography…etc.
Armed with this golden customer record with meaningful insights, you can anticipate clients’ needs and offer more personalized services or create a more memorable customer experience and build long-term relationships.
6. Poor Data Ecosystem:
You have a poor data ecosystem resulting in a lack of control over business processes. Business intelligence can’t be built on fragmented or dispersed data.
7. The evaluations of online and offline marketing data differ from your revenue data.
When you invest in various advertising campaigns with platforms such as Google Ads, Facebook, YouTube and banner and CPA networks, you get a bunch of colourful reports from your marketing (or outsourcing) agency showing that everything has performed great.
Traditional practice is to recall what you did last time or what your competitors are doing.
In absence of valuable, real time insights, organizations cannot make the right decision – means a data driven decision.
But to know what marketing efforts bring the most and the least profit to your company?
8. Lacking a clearly defined BI strategy
Organizations should proactively define the problems they trying to solve.
Only then they will be able to identify the right Business Intelligence solution that will suit their requirements.
9. Lack of Training & Execution
Many a times, companies might have well-articulated requirements, a sound BI strategy, and a good tool solution, but lack technical skills like designing, building, maintaining, and supporting BI applications. This results in BI applications to run slowly, break frequently, deliver uncertain results and eventually leading to rising cost of using the BI solution.
10. Lack of BI impact (Low utilization)
Management might always wonder why there is no change in business results attributable to BI and might feel that business value of BI investments not captured.
This indicates that the organization is not utilizing the BI solution at par with global standards and best practices.
This is because executives are unclear on how their company could benefit from BI.
11. Business Intelligence with unstructured data
Most of the times data is unstructured for BI to analyse. This leads to a problem when users need to perform simple BI Processes.
Businesses may invest in big data analytics but cannot complete the tasks in time. They may result to people spending hours on cleaning and structuring the data first and then using the BI solution.
12. Installation and Deployment
A painful BI solution installation and deployment would be difficult to maintain. Even an unplanned & rushed deployment would be unsuccessful so often. Doing this may leave users void with time to understand the system and develop the skills using the solution effectively.
13. Lack of company-wide adoption
Disjointed BI practices and failed universal adoption is a key business intelligence challenge. It’s essential to gain buy-in from all stakeholders early on in the process to get everyone on the same page.
14. Only Tech Teams Can Develop Custom Reports
A lot of traditional tools which allow analysing data and reporting are too complicated, so usually only tech teams can use them properly. And this is not the only one problem in this case — every time you need a report, you will have to delegate this task to your tech department. This means another waste of time.
15. Too expensive and hard to justify the ROI of BI
Budgets and resources are tight everywhere but especially for small businesses. The price of deploying BI is a primary concern among small and medium-sized enterprises (SMEs). SMEs are discouraged by the prohibitive costs of acquiring the right software. Also, limited resources make looking for qualified professionals such as data science experts, IT infrastructure professionals and consulting analysts impractical and worrisome. These deterrents are compounded by worries about expensive infrastructure investments needed to deploy BI software.
16. Businesses are not measuring the right indicators
Organizations are quick to measure financial KPIs, but unfortunately, they often stop there. While these metrics are important, they are often measured at the end of the year or quarter and are reactive in nature. Once again, they are crucial to measure and report on, but SMEs should be monitoring more. This is where a comprehensive BI plan contributes to an organization’s success. It is important that a wide range of appropriate KPIs are used to measure progress and performance. This data can be used to benchmark internally or across departments/offices. The data can also be used externally to compare a company’s performance against others in the industry.
17. Delivering mobile-based BI is no easy feat
We live in a mobile age. With more mobile devices in the world than human beings, gone are the days when producing work, planning, sharing information, or collaborating on projects was reduced to meeting rooms or desktop PCs alone.
Our hyper-connected shift into the mobile age means that there’s never been more demand for mobile-based BI solutions. But with business intelligence-based demand come business intelligence problems.
18. Providing true self-service analytics
One of the biggest BI challenges that today’s businesses face is reaping the benefits of genuine self-service data analytics solutions.
19. Dealing with the impact of poor data quality
It’s true that we live in the Age of Information, with more data generated in recent years than the rest of history. But while we are swimming in data, with this raft of insight comes saturation.
There is so much data available in today’s digital world that sifting through it and mining for the golden information that will help you enhance the success of your business is one of today’s most difficult business intelligence issues.
20. Sluggish query and database performance
Most irritating of business intelligence issues: sluggish query or database performance.
One of the most widely reported BI challenges to date, slow database performance leads to several internal challenges, including business intelligence security issues, fragmented processes, poor interdepartmental communication, and severe reporting lags. Naturally, none of these issues are good for business.
Regardless of your niche or sector, time correlates with money – which means that poor query performance or sluggish database responses will cost you dearly over time.
why is business intelligence important?
Business intelligence can help companies make better decisions by showing present and historical data within their business context. Business Intelligence is used to turn data into actionable information for leadership, management, organization and decision making.
A few ways that business intelligence can help companies make smarter, data-driven decisions:
- A company with a working BI strategy will have data that is accurate, complete, and organized.
- Harness the power of your data. Turn data into opportunity.
- Create a data-driven culture with business intelligence for all
- Gain Instant Access to Data Insights-Anywhere & Anytime!
- Identify ways to increase profit
- Optimize operations
- Predict success
- Spot market trends
- Discover issues or problems
- Analyzing customer behaviors, buying patterns and sales trends
- Measuring, tracking and predicting sales and financial performance
- Budgeting and financial planning and forecasting
- Tracking the performance of marketing campaigns
- Optimizing processes and operational performance
- Improving delivery and supply chain effectiveness
- Web and e-commerce data analytics
- Risk analysis
- Strategic value driver analysis
- Benchmark data against competitor and historical data for continuous improvements.
- Identify and analyze areas to cut costs and for budget allocation.
- Boost internal productivity by spending time on what is important.
process in BI
Business intelligence is the process of surfacing and analyzing data in an organization to make informed business decisions.
BI covers a broad spectrum of technologies and methods, from the way that data is organized and analyzed, all the way to how findings are reported. BI is used to answer how a business performed in the past and why those outcomes came about.
Execution of a successful business intelligence strategy requires a strong organization of how data is used from start to finish:
Data collection: A business needs to understand where they can collect data from visitors and customers, and how they can be organized into a form that can be analyzed.
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Data storage: Data relevant to businesses are numerous and often large in scope. In order to be useful, that data must be stored in a place that data stakeholders can reliably access, such as in a SQL database. A storage solution should always be up-to-date so that a company can act on changes in data quickly.
Data analysis: The core of business intelligence is focused on descriptive and diagnostic analytics, which answers questions of where your company has been, where it is now, and why things are the way they are now. BI tools need to be able to draw from data storage to conduct these different types of analyses.
Data reporting: All of our data and analyses will do no good if they do not reach decision makers and other stakeholders. BI should convey data and insights in ways that people with less context can still quickly understand and use them to make decisions.