In 2020, 54% of enterprises agreed that cloud-based BI was vital to their current and future initiatives. More than 46% of businesses already use a BI tool as a core part of their business strategy. So, what makes BI Strategy a critical ingredient in the recipe of success. The BI market will hit $33+ billion by 2025.

With the onset of COVID-19 and cloud-based solutions, we have witnessed a seismic shift in the work culture and incorporation of technology into the business strategies and business frames.

Today, most businesses are desperately searching for ways to stay competitive in the age of big data. One of the best ways to do this is business intelligence (BI). And while it is tempting to approach BI with a “throwing money at a problem” mentality, this is not the best use of resources. Instead, a well-considered and targeted BI strategy is the key to unlocking the value lurking in your data.

As businesses have realized the value of business intelligence, they also need to invest in it. But what is the best way to approach the BI strategy? Should you hire a consultant to design the perfect implementation, or should you take a more hands-on approach? How do you know which tools and technologies to use, and how do you put together a cohesive business case for investment?
Building a successful Business Intelligence (BI) strategy requires more than just developing a robust data analytics capability. It requires
understanding the goals of the analytics,

the role of the data in those goals,

and the priorities in place to ensure that the correct data is being used in the right way.

You cannot simply build a BI strategy and then expect it to work; you must build it with the intent of achieving specific, measurable goals.

Let us define Business Intelligence [BI] from scratch:

What is BI Strategy?

The BI strategy is the roadmap for achieving your business goals within your organization. It is the roadmap for mapping out how you will capture, store, and analyze data, defining how you will connect to data sources and load and transform data. Most importantly, the BI strategy defines how you will measure the success of your BI initiatives to determine whether the investments you are making are the correct ones.

A BI strategy enables your organization to achieve strategic goals using business analytics. The strategy should be the logical culmination of all the steps taken in the process of the data discovery lifecycle.
The strategy should identify the goals you want to achieve using your business analytics solution and the data requirements to achieve those goals. It should also identify the key performance indicators (KPIs) that will help you measure whether your solution achieves the goals defined in your BI strategy. It sets the direction for your BI investment, the vision for how you will use data to improve your organization, and it defines the objectives you will use to measure the success of that strategy.

Your BI strategy should be SMART:

Specific,

Measurable,

Attainable,

Relevant,

Timeframe.

BI Strategy involves:

Determining the goals, you want to achieve through your BI solution

Designing a solution that maximizes the value of your data

Defining the structure of the BI team, the roles, and responsibilities of the team members,

the metrics by which you will measure the success of the strategy.

Defining the scope of the BI team, and the budget that will be allocated for the team.

What makes the BI Strategy one of the critical elements in making data-driven intelligent decisions in the opulence of data floating around ?

BI is a strategic investment. It is a long-term investment and will take time to implement correctly.

Building a BI strategy is both theory and practice driven. The theory is driven by our understanding of business, challenges, and needs, and the practice is driven by your product, data, and operational maturity. The theory and practice are in constant flux as your BI strategy evolves.
A powerful BI strategy will provide the foundation for decision-making and continuously improving data usage, right from selecting the right data warehouse, data source, and the correct analysis and visualization solution. It involves aligning your data with the analytics and business needs of your organization,

enabling better data governance,

enabling better data analysis and better data enrichment,

providing better data discovery and enabling better data integration and transformation.

A BI strategy is also valuable for setting the direction of your organization. Let us get on board with 8 steps for creating a successful BI strategy.

Step 1: Define the Problem You Want to Solve with BI

Before you can build a successful BI strategy, you first must define the problem you are trying to solve. Most businesses end up building a BI strategy without having a clear idea of why they need it in the first place. It is essential to look beyond the obvious to unearth the valid reason your business needs to gather information from its data. Is your data lacking certain vital pieces?
It is also essential to start with an actionable goal. What do you want to achieve if you are trying to determine why your business needs BI? Your goal should be defined in a clear, concise, and unambiguous way. It should also be measurable.

Step 2: Get Input from Stakeholders for the BI Strategy

Once you have a clear idea of the data needed to achieve your goals, the next step is to get the input of your stakeholders. Your stakeholders will have a lot of valuable insight into your organization’s data needs, so it is essential to get their input.

The stakeholders you identify will include the data owners, data analysts, data users, business analysts, and others affected by your BI strategy. It is essential to get a wide variety of input from all these individuals because their input will help you determine the data requirements for achieving your goals.

You will need to identify the key decision-makers for your analytics strategies, such as the CEO, COO, and CFO, and get their input on your plan for data acquisition. You will also need to identify the other critical stakeholders in your organization, such as the data scientists, business analysts, and data engineers, and get their input on your plan for data acquisition. This step is critical because it will help you understand the needs and priorities of the people using your BI solution.

Step 3: Create a Plan for Data Acquisition

One of the most critical aspects of a successful BI strategy is data acquisition. There is no way to build a warehouse, data model, or visualize it without data.

Data acquisition refers to gathering data from various sources and putting it into a format that can be used in a BI solution. The success of your data acquisition strategy will determine the success of your BI strategy.

The first step in creating a plan for acquisition is to identify your key sources. You will need to know the specific data that your organization generates, such as sales, product, marketing, customers, revenue data, etc.

One of the most common mistakes made by BI analysts is collecting too much information. A successful acquisition plan is to identify the necessary data items for achieving your goals and then acquire only the necessary to achieve your goals.

You do not want to end up with a lot of data collecting dust, or worse, gathering digital dustbin. It is essential to define what is needed to achieve your goals and acquire only the required.

Step 4: Compare vendors

Once you have a plan for data acquisition, the next step is to identify the right vendors for achieving your goals. This step is often the most difficult for BI analysts because it requires you to step away from your analytics solution and evaluate it objectively. This is a complex decision, and there are many factors to consider.

The first factor to consider when evaluating vendors is the solution’s price. You will want to find a vendor who offers a solution at an affordable price for your budget.

You will need to identify several factors when comparing vendors, such as the data architecture, data governance, data quality, data security, and solution cost. It is essential to be objective when comparing vendors because a BI solution that is perfect for your organization may not be the best solution for every organization.

Step 5: Choose the Right Tools for the Job

Part of a comprehensive BI strategy involves choosing the right tools for your job. The right tools are not only essential for your data analytics job but for everything you do with BI. They are also an exceptional way to add value to your business.

The right tools for the job will make your BI efforts easier; the better they work, the more likely you will achieve your goals. The right tools can be classified into two distinct categories: technical tools (such as BI tools) and non-technical tools (such as analytic tools).

Ensure that the BI tool you choose is both flexible and robust to implement your BI strategy quickly and effectively.

Step 6: Develop an implementation plan

Once you have identified the right vendor for your analytics solution, the next step is to develop an implementation plan. Each organization is unique, and each business needs a customized solution for achieving its goals, so it is essential to tailor your implementation plan to your organization.

You will want to identify the critical components of your analytics solution, such as the data architecture, data governance, data quality, data security, and the platform. You will also want to identify the stages in the data lifecycle for achieving your goals and the data requirements for each stage.
This involves determining

which data items will be captured using your analytics solution

and then determining the schedule for capturing the data items.

Identify any external dependencies, such as the data warehouse,

and determine the timeline for building the data warehouse.

Identify any internal dependencies, such as the data lake, and determine the timeline for developing the data lake.

Step 7: Determine the Data Warehouse Design
Once you have identified the appropriate number of data collectors, the next step is to determine the data warehouse design. This involves determining

the data warehouse architecture,

the schema and the storage engine,

and the data warehouse technology.

Identify the appropriate number of data sources

and the number of data points you will collect.

Determine the number of intervals to collect data

and the number of data points each time.

Identify the stages in the data lifecycle for achieving your goals and the data requirements for each stage.

identify the key performance indicators (KPIs) that will help you to determine whether your BI solution is

The data warehouse is the central repository for your organization’s data. It is where all your data is stored, loaded, and analyzed, and it is where all the reports go.
It is the foundation on which all other data exploration and analytics are built. It is where data scientists and business analysts perform their analyses and where IT administrators and system administrators perform their day-to-day tasks.

Step 8: Determine the Scaling Strategy

Once you have an implementation plan in place, the next step is to determine the scaling strategy. This involves determining how you will scale your analytics solution over time and identifying the critical components of your scaling strategy.

You will want to identify the stages in the data lifecycle for achieving your goals and the data requirements for each stage. You will also want to identify the key performance indicators (KPIs) that will help you determine whether your BI solution meets your organization’s needs.

This involves determining the appropriate number of users for achieving your goals and then scaling your solution based on the number of users. You will also need to determine the appropriate number of data sources for achieving your goals and scale your solution based on the number of data sources.

Democratize data, empower the user, and drive innovation.

The key to unlocking the value of data within your organization is to democratize data. It involves breaking down the walls that separate data silos, so that data can be used and analyzed by all the users within your organization.

This empowers your users to make better decisions, enabling them to drive innovation by discovering new patterns, relationships, and insights within your organization’s data. Data democratization also empowers your organization to unlock the value of data by turning data into a competitive advantage.

As you have determined the critical elements of your BI strategy, it is crucial to evaluate them. Consider the potential benefits and challenges you will face when implementing your BI strategy.

Connecting the Data Points:

With 8 in 10 organizations that use BI for analytics having seen it work successfully, imagine a comprehensive partner that guides, empowers, and brings you the best of the world on the journey of BI Strategy. Softsensor AI is committed to intelligent and customized solutions that deliver value.

We believe with the right tools and years of unmatched expertise by your side. You can experience the revolution of positive change in every sector of your organization.

Equip yourself for the future with us!

Connect with us at vivek.gupta@softsensor.ai