Transform your business potential with Analytics, Data & BI

Data analytics and business intelligence (BI) are powerful tools that help companies make informed decisions and drive scalable growth.

However, for too long, these tools have been exclusive to data experts, which has prevented business teams and other members of the organization from being involved in the process and the benefit of being consistent.

Today, it is more important than ever that everyone in the organization can understand what is happening to the data as it moves through the Business Intelligence (BI) and analytics process.

This implies creating a management culture that establishes a solid data strategy and interprets data at all hierarchical levels, as well as establishing an adequate strategic plan.

Common mistakes that happen by not implementing an analytics strategy 

No control over the data 

What is not measured cannot be controlled; therefore, companies that do not implement a data analysis strategy may face problems when automating processes or making decisions, which in turn negatively impacts their operations. 

This can also have repercussions on a company's production and sales processes, resulting in financial losses and wasted time. 

Making decisions based on assumptions

Making decisions based on intuition or assumptions is a common practice in many companies, especially those that haven’t implemented a proper analytics strategy. 

This is because, in the absence of hard data, decisions are made based on experience. However, these actions, lacking real support, may be inaccurate and may lead the company down the wrong path.

To avoid this mistake, companies need to collect and analyze data in order to make fact-based decisions. By doing so, patterns and trends can be identified which can then be used to that can make predictions and make informed and accurate decisions.

No risk prevention

Most companies go through negative situations during their lifetime, either due to lack of knowledge, lack of experience, or making bad decisions. 

In this respect, business intelligence and data analytics can be very useful to, for example, identify potential customers, know the available market through potential market analysis, identify fraud patterns in terms of financial data (suspicious transactions or anomalies), identify and understand your customers' needs and respond to them, monitor the security of your information and prevent attacks, identify trends or changes in consumer behavior, etc.

All this can make a company better prepared to face possible problems or risks so that they can prevent them. 

Losing competitive advantage

Data analytics is a constantly evolving field, and companies that don’t keep up with the latest trends and technologies may lose their competitive edge. 

It is important to keep up to date in terms of analysis and technologies in order to make the most of the company's information.

One of the most important trends in this field is artificial intelligence and machine learning. 

Artificial intelligence allows companies to analyze large amounts of data and find patterns that would not be detectable by humans. On the other hand, machine learning is a technique that allows machines to learn from the data and improve their performance over time. 

Companies that are not using business intelligence-driven technologies are falling behind.

Another important trend in data analytics is the use of the cloud. More and more companies are moving information to the cloud in order to take advantage of the benefits of scalability, flexibility and accessibility. 

Main contributions of Analytics, Data and BI in companies

Better data quality

Data quality is essential to the success of any BI and analytics initiative. This requires the right processes and technology that enable the creation of clean, secure, consistent and connected data, which in turn, provides a solid foundation that drives descriptive analysis and organizational actions.

Poor quality data can lead to incorrect conclusions and, therefore, wrong decisions that can significantly impair business processes. 

To build a solid foundation, high-quality data must be guaranteed, meaning that the data must be up-to-date and accurate. Furthermore, it must be consistent across the organization and available in real-time so that it can be used to make decisions.  

Nowadays, the increase in data quality is 100% possible to obtain thanks to the use of technology and improvements in process efficiency that companies like London Consulting Group establish for organizations so that they can constantly improve.  

Use of business intelligence and reporting

Business intelligence and reporting allow decision-makers to look at aggregated data summaries to steer business decisions in the best direction.

For example, customizable dashboards can display information processed from multiple sources and reveal the most important KPIs, allowing executives to see how the business is performing in real-time from different perspectives or types of data analysis, and they can interact with the information anywhere and on any device.

Enabling innovation and generating conversations focused on discovering trends and business opportunities using data analytics is key to transforming a company and securing its position at the forefront of the market.

It is necessary to revolutionize the organizational culture, orientating it towards developing initiatives and projects that increase the organization’s agility, innovation and ability to make quick and assertive decisions.

Efficiency in management culture 

Analytics, Data and Business Intelligence (BI) enable a company to develop a management culture that focuses on using solid information for hierarchical data interpretation, monitoring, optimization and management.

Establishing an appropriate strategy begins with defining the company's objectives and understanding how data can help achieve them. This involves identifying what data is relevant to the business, how it is collected, and how it is used to benefit the organization's goals.

A management culture based on data science also implies creating a structured monitoring and management model that ensures accountability at all levels of the organization.

A commitment to innovation is an essential part of a management culture that is based on analytics and data. Therefore, it is important to foster conversations throughout the organization that aim to discover trends and business opportunities using data analysis.

How to implement data analytics in your company?

Implementing data analytics in a company requires a structured and well-planned approach. Here are the key steps to do so.

Step 1. Set clear objectives

Before implementing data analytics, it is important to establish clear and specific objectives. 

These must be aligned with the company's strategic objectives and must be measurable and achievable. 

This will allow the organization to focus on the important aspects of data analysis and to make informed and accurate decisions.

Step 2. Identify data sources

This is a crucial step in the implementation of data analytics. 

Companies need to identify all available data sources and determine which are relevant to their objectives.

These may include internal data, such as sales and financial data, as well as external data, such as social media and market data.

Step 3. Select analysis tools

Once the data sources have been identified, it is important to select the appropriate data analysis tools to collect, process, and analyze the information. 

These may include statistical analysis software, data visualization tools, and artificial intelligence and machine learning tools.

Step 4. Set up a data analysis team or seek advice

This team should consist of personnel trained in data analysis and they should have experience using the selected analysis tools.

In case your company doesn’t have experience in this regard, you can seek external advice through companies that use systems such as ERP, which is software with functions ranging from traditional financial and operations control, business intelligence, and sophisticated mobile solutions, to integration with "SCADA" (Supervisory Control and Data Acquisition) automation systems and customized developments.

These consulting companies usually provide a complete service when implementing data analytics; depending on the needs that the company has they can determine the actions or workflows and the project pilot, to the implementation. 

This is the only way you can be sure that the implemented actions and plan will be useful for data analytics and business intelligence.

Step 5. Develop action plans

Once the sources have been identified, the appropriate analysis tools have been selected, and a data analysis team has been established, it is important to develop an action plan. 

This plan should include the steps that are needed to collect, process, and analyze the data, as well as the strategies for presenting the results of the analysis to the company's decision-makers.

Step 6. Monitor and adjust

Data analytics is an ongoing and constantly evolving process. Therefore, it is important to monitor the results generated by the data analysis and adjust the action plan as needed. 

This will allow the company to adapt to changes in the market and to continuously improve its results.

Benefits of Analytics, Data and BI at different levels of an organization

The positive impact of analytics, data and BI spans different levels within an organization, making its application essential to the efficiency of multiple processes. 

Financial level

• Reduce costs by eliminating manual processes.
• Optimizes resources by preventing investment from being compromised by human error.
• It avoids the loss of information that can negatively impact the company’s finances. 

Technical level 

• It provides an up-to-date and reliable view of the current business situation and its interactions with key targets. 
• Identifies new strategic scenarios that are based on analyzing the variables. 
• It measures the current strategy’s progress and allows action plans to be modified in order to ensure that the objectives are achieved. 
• It allows the organization to identify new opportunities in a much more immediate and trend-aligned manner. 
• Enables the creation of the bases that facilitate scalable evolution. 

Tactical Level

• Enables the strategy to be translated into the department’s operational reality. 
• Identifies the behavior and trends of the operating variables over short periods, and their impact on results. 
• Implements a model that generates and controls specific and targeted action plans that improve results. 

Operational Level  

• Increased operational efficiency due to the disappearance of manual processes.
• Increases organizational performance and productivity.
• It improves the operational levels’ management abilities through the use of reliable information. 
• Catalyst for Agile and Collaborative (Multidisciplinary) Teams.
• Efficiently performs the processes of asking questions and finding answers automatically.

In conclusion, analytics, data and BI are critical to the success of any business in today's digital age. The ability to collect, store, analyze and visualize accurate and relevant data provides organizations with a scalable growth process. 

Furthermore, implementing a strong data management culture and an agile, user-centric approach to BI solution development can transform the way an organization addresses business challenges and generates value for its customers and shareholders. 

Analytics, data and BI are key enablers of competitiveness and business success in the 21st century, as they promote analysis and actions.

If you want to implement this within your company, contact us. At London Consulting Group we are experts in taking organizations to the next level. 

Sources:

• https://datascope.io/es/blog/principales-errores-en-el-analisis-de-datos/
• https://www.springboard.com/blog/data-analytics/data-analysis-process/
• https://www.fool.com/the-ascent/small-business/crm/articles/bi/
• https://kitdigital.online/blog/bi-analitica-importancia-inteligencia-negocio/