Every business data is divided into various silos. These data silos represent each department’s efficiency and capability to deliver. However, without an effective business intelligence strategy, the data that can be used for reinforcing processes will simply be lost.

Albeit that organizations of today have started to implement business intelligence tools. This allows organizations to consolidate important data and help them achieve higher ROIs. However, for effective implementation, organizations require a BI strategy roadmap.

It is not possible to devise a bi-strategy that is applicable to all. Yet, some pointers that will make the BI infrastructure pre-procurement and post-implementation more robust.

So to learn about business intelligence, and the key pointers, read ahead!

What is Business Intelligence?

Business intelligence is the strategy to harness insights from business data. An organization backed by BI (business intelligence) is capable of smart data-based decisions to grow. Upon giving data access to the BI tools, the tools turn these data points into reports, visualizations, summaries, dashboards, graphs, charts, etc.

What is an effective Business Intelligence Strategy?

Creating a business intelligence strategy that is effective requires planned efforts. The BI strategy should adhere to the company’s vision and goals. It requires the establishment of KPIs, defining stakeholders, assessing the business requirements, technological roadmap, etc.

Benefits of Business Intelligence

There are several benefits of using business intelligence within your organization. Below is the consolidated list:

• Ease of data-based decision-making
• Higher efficiency and productivity within the organization
• Ease of access to data even for non-technical users via dashboards
• Better customer experience and retention
• Better usability leads to higher employee satisfaction
• Higher credibility of data
• Better capabilities to compete in the market

Business Intelligence – Pointers for a Successful Implementation!

Below are the things for a successful business intelligence tool implementation. These are:

1. Infrastructural Compatibility

Before implementing a business intelligence tool, it is essential to understand whether it is compatible with the existing information system. A majority of large organizations today are using legacy systems. BI tools are expensive and are implemented in the entire organization. Make sure the deployed systems are useful for various stakeholders, are compatible with the existing infrastructure, and can be accessed company-wide with ease.

2. Find Sponsor

It is important to find someone on an executive level willing to support the implementation of BI. Once that is laid out, generate reports of the outcome and get them reviewed to showcase progress. It will maintain the trust of the sponsor.

3. Identify Stakeholders and Prioritize Business Goals

Before implementing a business intelligence tool, it is important to identify the associated stakeholders. A stakeholder would be anyone affected in any manner, post-implementation. Once that is established, ask employees about their problems and the types of analytics that would help them. The implementation of business intelligence shouldn’t be done from an IT infrastructure perspective. It is because almost every department can reap the benefits of a BI tool for smart decision-making. Once a list of requirements is created only then start searching for a relevant solution.

4. Assemble a BI Team

Handling company-wide business data isn’t child’s play. To harness the full capacity of a BI tool, a dedicated team is required. The team of business intelligence will understand the functional requirements of the entire organization. Once a team is laid out, they need to make sure further responsibilities such as:

• Management of the platform
• Managing the permissions, content organization, and creating groups of users based on the use case
• Constant integration of the BI tools with updates made to the architecture and workflows
• Data curation for relevant workflows, procedures, and processes

5. Employ a Chief Data Officer

Today, even the smallest of organizations are producing vast amounts of data. Data that is integral to the company process. Keeping that into perspective, large organizations are producing volumes of data that are incomprehensible. To employ effective data management policies, a chief data officer is required. A chief data officer will perform responsibilities such as:

• Strategic management of the data
• Establishing the key metrics and reviewing business performance
• Evaluating the effectiveness of business operations and making upgrades
• Figuring out patterns and relationships to establish trends from the company data
• Providing relevant information to the relevant stakeholders

6. Think about Compliance

Any organization dealing with huge volumes of data requires compliance policies. The policies should be laid before establishing the set of rules for collecting data, filtering, cleaning, or deleting it. A compliance strategy makes sure that no important data point is lost in the process, whether it be deleting or aggregating data. It establishes the safety and security of the data from massive anonymous data breaches that are an ongoing epidemic for many large organizations. 

7. Clean Data

As per a Gartner report, the financial implications of substandard quality data is $9.7 million annually. In fact IBM lost over $3.1 trillion dollars in the U.S. alone because of poor-quality data. Cleaning data isn’t easy, it requires solid quality data management. However, the idea behind clean data is to collect data points relevant to future processes and provide higher ROI.

8. Identify KPIs

Organizational data is divided into various silos, it is independent and not connected. These silos can be financial data, marketing data, HR data, etc. These data silos can be represented using multiple metrics to gauge the efficiency of the department. Once implemented, these silos help in figuring out places to improve. It also helps in a data-driven correlation between departments. For instance impact of increasing marketing budget on sales, increasing the number of resources leading to higher revenue, etc.

9. Reinforce Data Visualization

Data visualization is important considering the fast-paced industry dynamics. Consider it from the perspective of an executive who has to make several decisions in a day. Screening sheets of data isn’t the ideal way to do it. It would lead to missing important information and won’t paint a clear picture. However, visualized data is easy to digest and provides a concise picture of organizational data.

10. Procure with Ease

Often in the hurry to procure a solution, the procurement team misses out on multiple important requirements. To fix it, the procurement team should first understand what BI tools are. And what are they capable of? Once it is established, the procurement team should understand the requirements of the organization and its various departments. Based on that the team can pick a relevant solution that caters to all.

11. Collate Data Silos

Collecting and collating data are two very important functions of a business intelligence system. By collecting data from various silos and jolting it together, organizations are able to better understand the correlation. It leads to better decision making keeping the context in mind “what will happen if I take such and such action?”. Instead of pure speculation, one can create predictions based on informed data.

12. Effective Training & Change Management

In order to utilize any tool to its maximum potential, the team requires effective training. Effective training is part of change management where the management takes the initiative to educate the existing employees on how to use a particular asset. A majority of people aren’t aware of the full capacity of the tools implemented, thereby, often getting stuck or simply underutilizing it.

13. Create a Roadmap

Having a roadmap is essential. The new strategies are to be implemented along with the technologies that are in the pipeline for procurement. BI tools are simply used to aggregate data from various facets of an organization and represent them in a consumable manner. However, the roadmap created for the organization should synchronize with the BI infrastructure. It would make sure that the procured systems work with compatibility with the existing infrastructure.

14. Governance of Data

Governance of data establishes the effective usage of data “company-wide” for coming to a consensus. A BI tool implemented organization-wide promises higher visibility of data. In fact, it compels chief information officers to make decisions based on upgrades, improvements, and adjustments.

15. Be Ready for Change

The process of upgrading the existing BI architecture should be iterative. Once a system is laid out, the focus should be on constant changes to update the implemented system to achieve better ROIs. Every system at its implementation stage is in its beta phase. However post implementation, it becomes easy to visualize the changes required. Once those changes are certain, the systems should be updated with relevant upgrades.

Wrapping Up!

Every insight and prediction made in a company is extracted from historical data. An effective business intelligence strategy with an effective tool to help organizations what happened? It will help organizations reinforce their tactical, operational, and business strategies. By consolidating the company data and involving a meticulously created business intelligence roadmap, organizations can stand their ground and compete effectively with the competition. Without BI, it is simply impossible for any organization of today to sustain itself in the market and manage various facets such as budgets, operations, marketing, etc effectively.