Are you looking for the best way to build your business intelligence strategies? We explain techniques, roadmap, and examples of BI strategies in this article.
The worldwide economy has taken a significant knock in recent months, and businesses that have managed to endure are now searching for methods to use technological breakthroughs to advance. A business intelligence strategy is a roadmap that aims to assist businesses in measuring their performance and improving it through architecture and solutions. Business intelligence analyst abilities are at the forefront of BI plans, especially planning. So let’s get down to business.
Business intelligence strategies: Examples, techniques, roadmap, and more
You’ll need to get familiar with the terminology first! Business intelligence (BI) software collects business data and transforms it into practical insights that allow businesses to make educated business judgments. BI tools allow businesses to access and analyze data through reports, graphs, dashboards, charts, summaries, and maps to develop a BI strategy.
A business intelligence strategy is your roadmap for applying data in your organization. You’ll need a plan since simply adopting the appropriate technology and building a software platform won’t guarantee a profit. To develop a plan, you must first determine three things;
- How will you use the software platform?
- What data will you manage for analysis?
- And how will you enable your staff to make informed, data-driven decisions?
A business intelligence strategy can help your firm profit from actionable insights. Access to sales performance benchmarks, human resources salary projections, and ensuring your shipping department understands what to ship each day are just a few examples. A planned approach that includes discovery, planning, and measured execution leads to success.
Business intelligence strategies may help you think through all the elements of putting up business intelligence technology and executing everything from planning to objectives to personnel to ensure that your new solution is a success. It answers each area of how your firm utilizes data and each step in implementing a business intelligence tool.
Business intelligence techniques
Business Intelligence is concerned with assisting in decision-making. In reality, BI tools are frequently referred to as Decision Support Systems (DSS) or fact-based support systems because they provide business users with the technology to analyze their data and extract knowledge.
Business Intelligence tools usually access the data in a data warehouse. The explanation is simple: a data warehouse already contains data from numerous production systems within the organization, and it is cleansed, consolidated, conformed, and stored in one location. BI applications may focus on analyzing the information because of this. As a result, these BI applications are used for various business intelligence techniques.
Because data is stored as a set or matrix of figures, it is accurate but tough to understand. Are sales increasing, decreasing, or staying the same? Analyzing several dimensions of information at once becomes much more difficult. As a result, data visualization in charts is an easy approach to grasping how to interpret the data immediately.
Data mining is examining huge amounts of data to detect relevant patterns and rules using automated or semi-automatic means. When it comes to data, a corporate data warehouse possesses an enormous quantity. Discovering facts that may influence business decisions is very important. As a result, database researchers employ data mining approaches to reveal hidden patterns and relationships in the data. Knowledge discovery in databases comprises all of the steps involved in transforming raw data into useful information with any necessary selections, transformations, sub-sampling, and selection of the proper way for transformation.
Following the outbreak of the pandemic and the national lockdown that ensued, many businesses worldwide began utilizing cloud technologies in their operations. The advent of cloud technology has had a significant effect on many organizations. Even after the limitations are lifted, companies still prefer to work over the internet because of its ease of use and accessibility. Thanks to its low cost and easy-to-use features, even R&D projects are being transferred to the cloud.
We have already covered the pros and cons of cloud computing and cloud computing jobs if you are interested.
BI technologies help business users design, schedule, and generate performance, sales, reconciliation, and savings reports. BI technology-generated reports efficiently gather and present information to aid management, planning, and decision-making. Once the report is built, it may automatically be sent to a specified distribution list in the proper format with current/weekly/monthly data.
Time-series Analysis Including (Predictive Techniques)
Every data warehouse and business data is time-based. Product sales, calls, hospitalizations, and so on are just a few examples of this. It’s critical to show how users’ behavior has evolved regarding product relationships or sales contract modifications due to marketing campaigns. Future trends or outcomes may be forecast based on previous data.
Online Analytical Processing (OLAP)
OLAP (Online Analytical Processing) is a fundamental business intelligence approach that solves analytical issues with multiple dimensions. The multi-dimensional nature of OLAP allows users to examine data concerns from various perspectives, which provides flexibility in dealing with problems. They can find latent problems by looking at things from different angles. Budgeting, CRM data analysis, and financial prediction are examples of tasks that can be done using OLAP.
Extraction-Transaction-Loading (ETL) is a specialized business intelligence approach that orchestrates data processing. It extracts data from storage and converts it to the processor before loading it into the business intelligence system. They’re commonly used as a transaction tool, which transforms data from numerous sources into data warehouses. The data is then filtered and moderated by ETL to meet the demands of the business. It improves the quality level by loading it into end targets such as databases or data warehouses, called quality verification.
Data analysis begins with the mathematical underpinnings used to assess the significance and trustworthiness of observed connections. Distribution analysis and confidence intervals (for example, changes in user behaviors, etc.) are impressive features. The technique of using statistics to establish and evaluate outcomes from data mining is known as statistical analysis.
How to make a business intelligence strategy and roadmap?
Business intelligence strategies are on the rise. According to a recent study of over 700 business executives, 71% of firms have established a BI approach to anticipate company performance, improve client experience, gain a competitive edge, speed up data analysis, and make more data-driven decisions. So, how do they do?
Define the current state
Business intelligence strategies start with a baseline to know where you are going. Take, for example, if you realize that several departments have been using analytics. But the data has been mostly compartmentalized – marketing personnel doesn’t have access to sales information, and customer support is tracking user feedback for their internal purposes, or maybe there isn’t any analytics. It appears to function, yet how effective is uncertain.
The first step is to get the input of current BI processes’ users, as well as the IT team and department managers. As a result, you should be able to provide answers to the following questions:
- What is your vision for BI? Do you have one? Is your vision in line with your IT and corporate plans?
- Who are your BI players, and how well coordinated are they? Is there a lack of coordination between them?
- How do you plan, organize, and manage data? How can you help BI users?
- What solutions are you employing, and how? Which of them add value?
- Is your architecture in line with your company’s objectives? Are you confident that your licensing approach is the greatest option?
Then, to put it all together, compile a SWOT analysis to organize what you’ve discovered. The SWOT analysis, one of the most popular strategy-building tools, will aid you in determining your key assets and concerns for the following stage.
Create a BI vision
First, you must describe your present condition to understand your BI plan. Once you know where you are now, you’ll be able to define what is feasible. To begin, connect data from various sources to determine where you are right now.
Then, to assist you in better comprehending how BI may help your business succeed, create your objectives and priorities. After that, you’ll be on the road to establishing clear and reasonable expectations. It’s critical at this time to determine the following:
- What data will be collected?
- Who will be a part of the BI process?
- What is the best way to integrate BI with the company’s core business procedures?
- How can you provide BI solutions?
- Which BI solution should you use?
- What kind of KPIs do you need to keep an eye on?
- What is the future of BI lifecycle management?
Build a BI roadmap
A roadmap is a visual document showing the different implementation phases over time. By this step, you’ve already accumulated all of the data necessary to arrange and schedule on the map; all you have to do now is create time frames and deliverables for each activity. It is one of the most important topics for your business intelligence strategies.
A roadmap can cover only high-level activities such as “Find a BI vendor” or be focused on “Create a list of top ten best matches,” but for strategic mappings, the broad picture will be enough.
Assemble a BI team
BI specialists in charge of data discovery, analysis, and connecting it with end-users. There are numerous BI jobs and obligations for big businesses. They may be combined and concentrated in one position if you have a limited monetary constraint regarding human resources. If you want to establish your in-house team, consider the following key positions:
- BI project manager helps bridge the gaps between business and technology stakeholders by documenting, monitoring, and reporting IT service management processes.
- The BI architect established the BI infrastructure by converting business demands into a data warehouse.
- BI analyst is an analyst who uses data mining and analysis to extract valuable information.
- The ETL developer is responsible for the data warehouse’s ETL processes.
- An analyst in the field of data visualization is a person who provides informative and clear graphics to end users from the examined data.
- The system administrator is in charge of installing and maintaining the hardware.
Do you want to know how business intelligence creates collaboration?
Choose a sponsor
While a business intelligence strategy should include numerous stakeholders, selecting someone to lead the project is critical. Putting the Chief Information Officer (CIO) or Chief Technical Officer (CTO) is tempting. This isn’t always the best option. It should be sponsored by an executive with bottom-line responsibility, a broad view of the company’s objectives and goals, and a grasp of how to translate corporate goals into mission-focused key performance indicators.
CFOs and CMOs are ideal for implementation. They can lead the execution of a business case and be in charge of scope changes.
Define a budget
It’s time to consider a budget after establishing the company’s present condition. Developing an accurate budget is crucial in creating a successful business intelligence plan. Budgeting helps you distribute your resources effectively, so you have everything you need to start. Budget directly affects business intelligence strategies.
Several suppliers in the market provide various business intelligence tools that allow organizations of all sizes to use their data. Their prices, in most cases, vary from company to company, depending on their size and demands. This is why knowing your needs and how much cash you have is critical before looking for one of these alternatives. You’ll be able on this way to compare suppliers and select the finest one for yourself.
Choose a business intelligence solution
You will need help with your business intelligence strategies. Once you’ve completed your review of available data and demands, it’s time to pick a business intelligence solution and establish a data infrastructure that will last throughout the life of your strategy. Data collection and management, storage and capacity, visualization tools and dashboards, and access and governance, are all important areas to consider when setting up an IT architecture.
Do you want to know the 10 ways use business intelligence software in your organization?
Data collection and management
Keep your data gathering and organizing simple by keeping it straightforward. What do you need to know before you begin collecting data? Where will the data come from, and what kind and format will it be? Who will oversee and prepare the data? Who will ensure proper data entry and organization standards for data collection and organization? Will you have to hire any additional personnel to assist with your new data collection and management systems?
Storage and capacity
Fully evaluate your data storage alternatives, whether they’re off-site or on-premise. Your technical business intelligence team or even a business intelligence consultant will be able to advise you on the advantages and disadvantages of each storage solution in terms of your company objectives.
Data visualization tools and dashboards
Any successful business intelligence strategy necessitates the delivery of insight via data visualization and visual analytics dashboards. You’ll know what dashboards and visualization tools best suit your organization’s needs when you decide the scope of your business intelligence strategy and the intended internal audience.
Data access and governance
The data access and governance rates required for your new business intelligence approach should be discussed with your CIO, CDO, or another technical team in charge of the BI program.
- Should you provide more access to certain individuals or executives than others?
- What data will each user or employee have access to, and who will be allowed to change the actual data?
- What safeguards do you need to secure your business intelligence solution from external security risks?
- Will the selections you’ve made in access help or hinder your company’s goals and efforts to become a data-driven organization?
- How can we ensure appropriate data sharing and governance in the face of inevitable changes in employee attitudes?
You can check the top 20 BI tools.
Document a BI strategy
It is a strategy document intended to serve as a resource for the entire organization and as a point of reference for the strategy presentation. It includes these elements:
- Executive summary
- BI strategy alignment with corporate strategy
- Project scope and requirements
- BI governance team
Develop a “Data Dictionary”
Large data dictionaries may be time-consuming and difficult to maintain, so they are now considered a faux-pas in Agile development. It’s too easy for large data dictionaries to become cumbersome and hard to keep up with. That said, for business intelligence to flourish, there must at the very least be a general agreement on data definitions and mathematical computations. The absence of a nomenclature agreement is an issue affecting many businesses today. For example, finance and sales may use the term “gross margin” differently, resulting in a mismatch between them. To prevent this from happening, get all of your SMEs to sit down and hammer out the definitions. Then pick the repository that’s best suited for your company to store this data.
Providing a company-wide BI strategy in most situations entails giving new tools to non-business intelligence and data analytics users.
Employees at all levels should feel confident in their ability to use the new solution to inform their everyday decisions without difficulty. Employees shouldn’t struggle to use your business intelligence solution; most of that ease and confidence come from effective, thorough training.
Launch and measure
Congratulations, you’ve completed the process! After all of your research, planning, question asking, aligning, and collaboration, you’ve created a business intelligence strategy! Remember to track your progress and keep measuring after each phase of your plan; we suggest informing workers when you meet your company goals and achieve them in an evidence-based manner. Take them with you on your journey to success, and measure that success meticulously so that you can tell stakeholders and everyone else in your team about it.
Effectively implementing a new business intelligence solution is not easy. Still, with the right approach, you can keep track of your timeline and goals while simultaneously getting more done for your organization.
Measuring effectiveness with business intelligence strategies
For most BI managers, assessing success is a postscript. Getting permission for a project and delivering results without creating another project to evaluate team performance is difficult enough. And if you do have the time and inclination, exactly what do you track?
These are some options for it:
- Usage tracking
- Social media analysis
- Cost efficiencies
Real-world business intelligence strategy example
Let’s see some BI solutions in action:
New York Shipping Exchange: BI Reduces IT Dependency
The New York Shipping Exchange (NYSHEX) is a shipping-technologies firm striving to improve the process of exporting goods from the United States.
- Challenge: To make sense of the whole company’s performance, NYSHEX would need to manually extract data from its proprietary and various cloud applications and then import it into Excel. This was a time-consuming process; few individuals had access to the information, and most report requests were passed on to the engineering team to fulfill.
- Solution: They invested in BI, centralized their data, and provided everyone in the company with analysis tools that even non-coders could use.
- Results: In 2019, the firm more than tripled its shipping volume from Asia to the United States due to business intelligence and other efforts.
Expedia: BI Builds Customer Satisfaction
Expedia is the parent business of several top-tier travel firms, including Expedia, Hotwire, and TripAdvisor.
- Challenge: Customers are critical to the company’s goal, strategy, and success. The online experience should provide a similar level of satisfaction as a good trip.
- Solution: The firm had a large quantity of data to aggregate manually, leaving little time for analysis. The client satisfaction team used business intelligence to analyze customer data from the company and link findings with ten corporate objectives that were directly linked to the goals. Owners of these KPIs collect, organize, and analyze data to identify trends or patterns.
- Results: Customer support can access real-time performance data and take corrective actions if necessary. In addition, the information may be utilized by other departments. A travel manager, for example, might utilize BI to discover high volumes of unused tickets or unbooked reservations and devise methods to modify behavior and enhance overall savings.
Sabre Airline Solutions: BI Accelerates Business Insights
Sabre Airline Solutions offers booking solutions, revenue management, web, mobile itinerary applications, and other technology to travel sector businesses.
- Challenge: The travel sector is fast-paced, to put it mildly. Clients in the industry required advanced solutions that could give real-time information on consumer habits and actions.
- Solution: Sabre created an enterprise travel data warehouse (ETDW) to store its vast quantity of data. With a 360-degree view of company health, reservations, operational performance, and ticketing in user-friendly environments, Sabre executive dashboards provide near real-time insights.
- Results: The ability to scale, a user-friendly graphical interface, data aggregation, and collaboration have resulted in increased income and client happiness.
Businesses need a BI strategy to advance and maintain their competitive advantage. Companies must acknowledge the value of information customers give so that they may change their long-term vision and gain a fresh perspective to stay up with changing consumer behavior in the market.
We’ve addressed what a BI plan is and why it’s significant. This raises an issue: Do you really need one? If you want to stay on top of changing client behavior, maintain your company’s competitive edge, and remain one step ahead of your competitors, we would say yes.
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