Overcome Common BI Implementation Challenges [A Detailed Guide]

Overcome Common BI Implementation Challenges [A Detailed Guide]

Your consumer behavior is shifting. Your old operational playbooks may no longer work in a rapidly evolving landscape. You have to make decisions, you have to make them fast, and you need to make sure that your decisions are backed by hard data.

Making data-driven decisions on the go is vital for enterprise success in these times of flux. As a result, companies of all sizes are either heavily investing in BI (Business Intelligence) reporting solutions or planning to do it soon. The end goal is to combine siloed data from multiple sources and make decisions based on a single source of truth. In fact, the global BI market was estimated at $23.1 Billion in 2020 and is projected to be valued at $33.3 billion by 2025. Not only big firms but even small and mid-sized businesses are using BI tools to inform their business strategies.

However, simply making the investment is not enough. Implementing state-of-the-art BI solutions require organizations to relook at their ways of working. No BI implementation can be successful if it does not have the buy-in from its actual intended users – your business teams. As humans, we are all resistant to change – and overcoming that resistance is the starting point of your BI implementation strategy.

Your BI investment cannot generate the expected results if the implementation isn’t fool-proof. To maximize the impact of your investment in BI and other reporting tools, you need to identify the organizational hurdles along the way and build strategies to address them from the get-go.

Common BI Implementation Challenges and How to Avoid them

Although companies are fast-adopting BI and reporting solutions, it is still a brand-new territory for many. A Gartner report indicates that a staggering 70-80% of corporate business intelligence projects fail. Some common reasons include poor communication among teams, inability to identify the business requirements, and IT employees approaching BI as an engineering solution. As a result, many companies are not able to realize the full potential even after investing in a robust solution.

Let us explore some of the pervading BI implementation challenges and how you can address them.

1. Not identifying the business problems you want your BI initiative to address

Is BI investment a lucrative deal? Yes. But not identifying your enterprise goals before integrating the solution into your workstreams can be a tricky approach. There are numerous options available in the market and finding the right solution can be a hassle. Looking for a one-size-fits-all solution is a common mistake and one of the primary reasons why BI investments fail.

Choosing the right software that answers your organization’s unique reporting and analytics needs is crucial to making the most out of your BI investment. You need to clearly crystallize the business problems you need to address and purchase BI tools that answer those unique problems.

2. Not involving business users in the decision

A common mistake enterprises make when investing in a BI solution is looking at it as a technical project. Truth be told, analytics and reporting are business needs. These tools need to be a part of critical projects across departments and workstreams. Business intelligence is simply not an IT initiative but a business-oriented one. You need to engage your business users from the get-go and understand the specific requirements of their workstreams. Ensure that your BI solution addresses these needs.

The next step is to create and maintain active engagement on your BI solution from your business users. Inform them about the benefits of the BI tool and why they would want to use it. Highlight the advantages in a way that addresses their business unit’s performance and tell them the complete story of how the investment will enhance the way they use data for decision-making.

3. Investing in a code-led BI platform

Investing in a code-led BI platform increases the reliance on IT and data engineering teams to make sense of the data and create the simplest reports for decision-making. The process can be bureaucratic, highly dependent on other business functions, and time-intensive. This beats the very purpose of investing in BI tools for quick decisioning across the board.

More and more new-age, data-obsessed organizations prefer implementing a low-code or no-code BI tool for their business users with minimal IT skills to perform rapid reporting and decisioning-on-the-go.

Low-code BI platforms also make data orchestration and analysis happen literally at the click of a button. Their seamless UX makes these platforms a favorite among business users.

4. Not aiming for a single version of truth

Investing in different BI tools for various use cases and users creates data silos. As teams use specific tools across departments, they prepare individual reports that they share only among themselves. Each team is sourcing data from different pools, preparing reports their own way, and making decisions on the basis of these far-from-holistic reporting mechanisms. Eventually, there is no single source of truth across the enterprise.
Businesses should consider implementing a single BI tool by identifying business problems across departments and prioritizing problems that align with enterprise goals.

5.Using outdated data for reporting and decisioning

Not every business intelligence tool comes with the functionality of regular data updates. Outdated data hampers the bottom lines in the form of inaccurate reports and misinformed decisions. At the end of the day, your business report becomes invalid, and you don’t achieve the business outcomes you had set out to, with what you thought were informed decisions.

It is important to invest in BI tools and reporting solutions that provide real-time information or perform frequent data updates automatically, allowing users access to reasonably fresh data at all times. This is crucial for creating accurate reports, making data-informed decisions, and deriving a competitive edge from your BI investment.

6. Not making the optimal build vs. buy decision

The ‘build vs. buy’ debate in the BI context is not new. Whether your business should buy a pre-packaged solution or build a business intelligence system is a question that all organizations grapple with when they take up the BI investment project. Organizations perceive their business processes as unique and end up deploying in-house, custom-built BI solutions due to the perceived lower pricing. However, they couldn’t be farther away from the truth.

The reality is that the majority of business processes across enterprises are similar, with likewise needs and intended outcomes. A pre-built solution with minor customizations seamlessly addresses the specific business requirements at minimal risk. Moreover, an intelligent BI tool provides access to proven approaches that are generally outside the scope of an in-house solution. Therefore, enterprises should evaluate pre-packaged, scalable BI solutions that deliver out-of-the-box KPIs and operational reports while also allowing ad-hoc changes as and when the business needs them.

BI implementation is hard work

But with the right BI partner, you no longer have to go it alone.
Enterprises today have access to an unprecedented amount of data. That being said, data analytics and reporting are no walks in the park. Companies invest in BI to analyze data and extract actionable insights. And they spend reasonable budgets on this enterprise-wide project. Choosing the right BI implementation partner becomes vital in order to maximize the ROI from BI implementation.

With SplashBI, you can put the power of reporting and analytics in the hands of your end-users. As an enterprise-ready ad-hoc business intelligence solution, SplashBI can be deployed on-premises or in cloud, depending on your unique business needs. You can now confidently make critical business decisions, courtesy of a large library of 2000+ pre-built reports and visualizations on the go. With hundreds of BI implementations under our belt, we truly understand the potential pitfalls and roadblocks. Both our product and our implementation teams know how to address these barriers.

Make a smart investment with SplashBI and steer clear of BI implementation mistakes. Get in touch for a demo.

Frequently Asked Questions
How do I ensure data accuracy and reliability when creating analytical reports from multiple data sources?
SplashBI ensures data accuracy by collaborating with business users for data validation across integration systems. It harmonizes multiple data sources into a single trusted view, applying standardized rules and validations via the SplashHR Data model. This includes periodic data quality audits and cross-referencing financial with non-financial data for reliable analytical reports.
Why are real-time analytical reports essential for modern corporate financial planning and analysis (FP&A) processes, and what risks are associated with relying on batch reporting?
Real-time analytical reports are essential for modern FP&A to enable faster, confident decision-making and ensure data accuracy by providing a unified financial view. Relying on batch reporting risks poor data quality, lack of trust, and significant delays, as seen in financial close processes reducing from 3 weeks to 7 days with real-time SplashBI reporting.
What are the common challenges in building and managing analytic pipelines?
Common challenges in analytic pipelines include data quality issues like incomplete or inconsistent records, fragmented HR data across multiple platforms, and the inherent difficulty of merging disparate systems. SplashBI's Data Pipeline addresses these by seamlessly integrating data with a no-code, fully automated experience, including AI/ML capabilities.
How do you get business user buy-in to prevent BI implementations from failing?
To ensure business user buy-in for BI implementations, SplashBI emphasizes early stakeholder engagement to align project objectives with business outcomes. This involves regular update calls, robust end-user training, proactive demos, feedback sessions, and dedicated Go-Live support. Providing role-based dashboards and intuitive self-service capabilities also drives adoption.
Build vs. buy: should you build BI in-house or buy a pre-built BI solution?
The build vs. buy decision for a BI solution depends on factors like expenses, support, coherence, scalability, and connectivity. Building in-house offers control but is costly and time-consuming. Buying a pre-built solution, like SplashBI, provides faster value with pre-built connectors, reports, and data models, reducing startup and maintenance efforts.
What common challenges does a BI Center of Excellence help overcome?
A BI Center of Excellence helps tackle common data headaches like poor data quality, scattered systems, and slow reporting. It empowers teams with better analytics, self-service tools, and ensures data is secure and aligned with business goals. Essentially, it builds trust in data and makes it easier for everyone to get the insights they need, faster!

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