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The Importance of Data Intelligence in Business Management is Increasing!


The Importance of Data Intelligence in Business Management is Increasing!

In today's business environment, technology is the key to driving success. To stay ahead of the competition and meet customer demands, organizations need to modernize their processes with a focus on data intelligence and advanced analytics.


It didn't happen overnight that the use of data intelligence became a key strategy for companies trying to stay competitive in the marketplace, and we can no longer ignore it: We are increasingly focusing on relevant and intelligent management that seeks out data targets.


Write this tip! Through the analysis of information about your business, it is possible to make informed and more ambitious decisions, optimize processes and gain a range of competitive advantages.


What is Data Intelligence


Companies in different segments use data intelligence as a decision-making strategy. For example, an e-commerce company can use user behavior data analytics to identify consumption patterns and offer personalized products based on customer preferences. On the other hand, a telecommunications company can use data analytics to identify consumption trends and offer plans better suited to customer needs.


The latest definition of data intelligence includes the steps of collecting, organizing, analyzing and interpreting information relevant to business decision making. From this concept it is understood that data intelligence includes a set of collection actions for a technology company, which may be completely different from, for example, the collection actions of a shoe company. It all depends on micro and macro targets, success indicators and planning for each sector.


That's why advanced analysis is an effective method! With it, you can review large volumes of various data and gain valuable insights.


In a business context, advanced analytics technology has become critical as data throughput increases, especially in day-to-day operations and customer interactions.


And where does this data come from?


This information that will serve the analysis can be obtained from different sources. With the adoption of smart and networked technologies in most business processes, it is much easier to access a complex database full of good information! Here are some interesting options to explore if they apply to your segment:


• Sales data such as sales made, value, quantity, location, period, type of product or service;

• Customer data such as age, gender, location, purchasing behavior and purchase history;

• Inventory data such as quantity of available products, time in inventory, inventory movement;

• Production data such as the production of goods or services such as production time, associated costs and quality level;

• Marketing data such as advertising campaigns, social media and events;

• Financial data such as the company's financial health, revenues, expenses, cash flow and profitability;

• Competitive data such as competitor strategies and performance, pricing, products, services and marketing;

• Customer feedback gathered from satisfaction surveys, comments on social networks and complaints.


Benefits of advanced data analytics for your business

In simple terms, companies can often avoid decisions based on assumptions or intuition that may be wrong or outdated, and can leverage the intelligence generated by their internal processes to improve their performance. With accurate and up-to-date information in hand, decisions can be more informed and strategic, resulting in increased efficiency and productivity of the company.


At this point we can consider internal and external performance:


Internal: data intelligence can help companies identify bottlenecks and improvement points in internal processes, allowing for the optimization of these processes and an increase in the efficiency of the company as a whole. Adopting smart systems also helps automate routine tasks, freeing employees to focus on more strategic initiatives.


External: This approach provides valuable insights. With this, it is possible to identify market trends that allow the company to adapt to market demands and offer products and services more suited to customer needs.


Challenges in implementing data intelligence


Despite the advantages of using data intelligence, implementing this strategy can present some challenges.


Data access and quality: For data intelligence to be effective, there must be access to accurate and up-to-date data. Companies often struggle to obtain quality data and efficiently integrate it into their operations;


Technology and infrastructure: Implementing data intelligence-driven processes requires adequate technology and infrastructure for data collection, storage, processing, and analysis. Companies may face challenges in choosing the right tools and integrating them with their existing systems. It is also necessary to ensure data quality and information security, and this may require investment in technology and staff training;


Ethics and Data Privacy: The previous topic brings us to it and the next! Data collection and analysis also presents ethical and privacy issues, especially with increasing data regulation around the world. Companies need to be aware of applicable laws and regulations and ensure that their processes comply with them.


Skills and abilities: Data analysis requires specific technical skills, including statistics, programming and data analysis. Companies may struggle to find and retain talent with these skills;


Organizational culture: Implementing data intelligence-driven processes may require changes in the company's organizational culture, including the way people think and make decisions. To ensure that the organizational culture supports the implementation of processes driven by data intelligence, it is important that company leadership is involved and committed to change.


Intelligence about connections

I couldn't finish this post without mentioning a very important part in this discussion: selling. The connections that connect your brand to suppliers, partners and customers occur in the sales industry. In addition, the connections and networking data generated by employees and vendors can provide valuable information for your company! This data can help your company to:


Sales Improvement: Identify additional sales opportunities. For example, if an employee connects with someone who works at a company who could be a potential customer, you can use that information to start a conversation with that company about their needs;


Enhanced Collaboration: Enhance collaboration across teams and departments across the organization. By identifying how people connect, the company can create opportunities for teams to work together and share knowledge;


Identifying trends: Identify trends and changes in an industry or market. You see, if a large number of employees and salespeople are connecting with people from a particular company, it could be an indication that the company is gaining prominence in its industry;


Identifying gaps: Identify skills or knowledge gaps within the company. If many employees connect with people with certain skills that the company lacks, the company may consider hiring someone with those skills;


Influencer ID: Reveal influencers in your industry. They can be contacted and used to promote the company's brand and products.


The connections and networking data generated by employees and vendors can provide valuable insights for a company, and we have a powerful and complete tool to help you with that task! Trowas Digital Business Card has been developed for companies that want to increase the performance of their teams through data analysis and performance tracking.


This is especially important in an increasingly competitive and uncertain world where companies must make fast and ambitious decisions to stay viable in the marketplace. If you are not yet using data intelligence in your company, it is time to see this technology as an ally for the success of your business.


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