Blog

Blog

Category: Blog

Your blog category

bysira4

Why Every Business Needs Advanced Analytics to Stay Competitive in 2025

In modern times, staying ahead is not just about hard work. It is about using data wisely. Advanced analytics gives your business an advantage whether it is improving customer service, saving money or planning for the future.

It is no longer just a useful tool. It is something every business requires to stay competitive.  The advanced analytics help you stay competitive and position your business for success. In this post let us see why every business needs advanced analytics to stay competitive!

The Data Explosion

Businesses generate and collect more data every day nowadays. Over 328.77 million terabytes of data were generated daily in 2023. This amount is predicted to grow rapidly. It will create 175 zettabytes of data in 2025 based on several researches. This large amount of data provides opportunities and challenges for businesses. Businesses that connect this information can gain valuable insights that drive innovation and enhance administration.

Top Advantages of Advanced Analytics

Advanced analytics turns raw data into relevant insights. This offers strategic decisions and improves operational efficiencies. Below mentioned are several reasons why businesses must adopt advanced analytics to stay competitive:

Improved Administration

A study showed that 87% of business owners trust data analytics is important to achieve growth and innovation. Advanced analytics enables organizations to make better decisions based on real time data. This approach eliminates the need to depend on intuition or incomplete information. This shift allows companies to respond more effectively based on market changes and customer needs.

For example, businesses utilizing advanced analytics can identify trends in consumer behavior. This allows them to adjust their plans accordingly. Retailers can analyze purchasing patterns to optimize inventory levels. Manufacturers can use predictive maintenance analytics. This helps to reduce outage and improve production efficiency.

Building Future Success with Predictive Analytics

Predictive analytics examines historical data to anticipate future trends and behaviors. In future 40 percent of businesses will use predictive analytics to assist their strategic decisions. This capability enables organizations to predict customer preferences. It also helps maximize inventory management and tailor marketing campaigns effectively.

A study showed companies using predictive analytics in their marketing efforts experienced a 10 to 20 percent rise in sales. This is when compared to those that did not. Retailers can predict demand fluctuations and adjust their stock levels accordingly. This helps reduce waste and improve customer satisfaction.

Real Time Insights

The capacity to analyze data in real time is becoming important for your businesses across various sectors. Real time analytics will reconsider how organizations make decisions by 2025. This allows them to act swiftly on growing trends and opportunities. Technologies like cloud computing and AI-powered analytics tools allow this transformation. This enables businesses to track operations continuously and respond immediately to changes in the market.

Based on a report companies that implement real time analytics can achieve a 20 to 30 percent improvement in operational efficiency. For example, logistics companies can track shipments in real time. This optimizes delivery routes based on traffic conditions and reduces costs.

Improved Customer Experiences

Advanced analytics empowers businesses to personalize customer interactions. It does so by analyzing customer preferences and behaviors. Companies using data focused insights can create customized experiences. This helps enhance both customer satisfaction and loyalty. A report indicated that 63 percent of organizations plan to increase their investment in data analytics powered by AI. This recognizes the importance of giving personalized services that match individual customer needs.

Several businesses have successfully utilized advanced analytics. It helps to recommend products or content based on user behavior. This significantly enhances user engagement and conservation rates.

Major Role of Artificial Intelligence and Machine Learning 

AI and ML enable deeper insights and more accurate predictions. These technologies automate complex processes. This allows businesses to analyze vast datasets quickly and efficiently.

Market Growth 

The AI market globally will achieve billions of dollars in 2030. In future it grows at a compound annual growth rate of 36.6 percent from the year 2024 to 2030. This growth shows the expanding dependence on AI technologies in various industries.

Enhanced Accuracy

Machine learning algorithms enhance prediction accuracy by recognizing patterns in large datasets. These patterns may be difficult for humans to detect. This ability results in more effective strategies at every level of the organization.

For instance, financial institutions are using AI-driven algorithms for fraud detection. It is done by analyzing transaction patterns in real time. This significantly reduces losses due to fraudulent activities.

Creating a Culture Based on Data

Organizations must build a data focused culture to fully use the power of advanced analytics, where decisions are based on evidence rather than just intuition. This involves training employees at all levels on the importance of data literacy. It also encourages collaboration between departments.

Companies can open up innovative solutions and drive continuous improvement across all areas of the business. This is done by promoting an environment where employees feel empowered to use data in their daily tasks.

To Sum Up

The need for advanced analytics will only increase in the upcoming years. Organizations that adopt these tools will be better positioned to go through the complexities of the modern business world. Businesses can enhance administrative processes, improve customer experiences and ultimately drive growth by using predictive analytics and AI technologies.

Investing in advanced analytics is not merely an option in a world where data reigns chiefly. It is a necessity for any business looking to stay competitive in this competitive world. The future belongs to those who learn their data ensuring they not only survive but succeed in the years ahead!

bysira4

Unlocking Business Potential: The Transformative Power of Data Analytics

In today’s data-driven world, businesses seek new opportunities to thrive, compete, and innovate. There is no doubt that data is the lifeblood of businesses today. Businesses worldwide use data analytics to find hidden patterns, predict trends, and drive strategic growth.

Studies reveal that organizations using advanced analytics are 5x more likely to make faster decisions. Data analytics holds the key to a smarter and more profitable future. But how can businesses unlock their full potential? Continue reading to know more.

Utilizing Data Analytics for Business Growth 

In a dynamic business environment, companies that are effectively utilizing data analytics can make the right decisions. It will enhance customer satisfaction and drive business growth. Here is how data analytics allows businesses to lead the market: 

  • Analyzing various data sources helps identify patterns of customer demands. Predictive analytics enables businesses to adapt strategies based on future market trends. 
  • Data Analytics helps find customer segments and new market opportunities. Businesses can use feedback and sales data to improve current offerings and innovate new ones. 
  • Data analytics gives access to real-time analysis and enables impactful decisions. Companies utilizing data analytics adapt to market changes faster and stay ahead of competitors. 

Using data analytics, businesses can turn raw data into valuable reports. These reports will help businesses to improve operational efficiency and achieve long-term profitability. 

Analyzing Customer Behavior

Data analytics has become a crucial tool for businesses aiming to understand their customer behavior and preferences better. When analyzing patterns in customer data, companies can gain valuable reports on what drives their audience.

Businesses can find out where they lack and what customers really want. This knowledge helps businesses to personalize their products and services to improve customer satisfaction. This improvement will build lasting customer loyalty. 

Data Analytics for Smarter Decisions 

Business environments often change with many trends and market demands. Data analytics helps businesses make the right choices with access to real-time insights into market trends and customer feedback. With this, a business can confidently launch new products and refine their pricing strategies.

These data analytics reports help businesses identify possible growth opportunities, too. Notable benefits of data analytics report for businesses include: 

  • Data-backed decision-making for greater accuracy 
  • Quick identification of emerging opportunities 
  • A clear understanding of customer needs to stay ahead of the competition

Driving Personalization and Customer Engagement

Businesses utilizing data analytics will deliver personalized interactions suited to individual customer preferences. Companies can craft personalized marketing campaigns and recommend products based on past customer purchases using customer data. They can also provide customized support to meet their unique needs. 

These personalization actions will result in deeper customer engagement and build lasting loyalty. For instance, a personalized email campaign featuring product recommendations based on previous purchases can make customers feel valued.

Similarly, offering real-time support personalized to their queries enhances satisfaction and trust. Customers today highly expect businesses to address their needs. Data analytics becomes a crucial tool for building stronger relationships and driving long-term success. 

Focusing on what customers truly want supports your businesses in positioning themselves as a customer-centric brand. This approach leads to high retention and an added advantage in a crowded marketplace. 

Focusing on operational efficiency

Efficiency is a crucial part of every successful business. Data analytics takes a major part in achieving it. Examining operational data helps companies to find inefficiencies and update their processes. Businesses can utilize data analytics reports to maximize their resource allocation. These analyses enable businesses to improve productivity and their overall performance. 

Identifying Bottlenecks in Processes 

The first step in optimizing the business operations is identifying bottlenecks. This means finding areas where processes slow down and encounter interruptions. Using data analytics, businesses can pinpoint these problem areas and address them effectively. Common bottlenecks include: 

  •  Manufacturing delays can disrupt production timelines and delivery commitments. 
  •  Inefficient transportation and inventory management may drive up costs and diminish customer   satisfaction. 
  • Slow response times can result in unhappy customers and missed business opportunities. 

For example, analyzing data from a production line helps businesses discover which specific machine frequently causes delays. Addressing this issue through quick fixes can significantly enhance production efficiency.   

Resource Allocation 

Once bottlenecks are identified, reallocating resources effectively becomes the next important task to be done. This involves ensuring the right distribution of staff and materials to optimize operations.

Businesses can redistribute staff and introduce some automation tools if a customer service team is overwhelmed. These steps will help balance the workload and improve response times. 

Resource optimization also extends to inventory management. Businesses can ensure they stock the right products in the right quantities using data analysis. It will reduce waste and improve cash flow. This approach minimizes unnecessary expenses and maximizes operational efficiency.

Building a Data-Driven Culture

Building a data-driven culture is important for organizations looking to utilize the full potential of their data. This approach supports decision-making at every level. This data-driven culture encourages innovation and growth. 

  • Provide training to equip employees with the skills to interpret and use data effectively. 
  • To promote continuous learning, keep teams updated on evolving data tools and trends.  
  • To facilitate teamwork, encourage departments to share insights and data. 
  • Embed data analytics into business strategies for more detailed planning. 
  • Encourage analytical thinking through all roles to enhance decision-making processes. 

Try to prioritize data literacy and collaboration. This strategic alignment helps organizations cultivate a culture where data allows informed decisions, leading to greater success and innovation.   

Enhancing Overall Productivity 

The main goal of data-driven optimization is to enhance productivity. Businesses can use data analytics to monitor performance metrics and implement real-time adjustments. This leads to: 

Increased output – Modernized processes enable businesses to achieve higher production levels with no additional costs. 

Higher employee satisfaction – Efficient resource allocation reduces stress and builds a more balanced work environment. 

Better customer experiences – Faster response times and smoother operations translate to improved customer satisfaction and loyalty. 

Wrapping up

Data analytics drives personalization and optimizes operations to build a robust foundation for your business’s success. Data analytics helps businesses to predict future customer needs and dynamic market trends.

Identifying inefficiencies and optimizing operations help companies to make the most of their efforts. Businesses prioritizing data-driven decision-making are better equipped to thrive in a competitive market and achieve long-term growth.

bysira4

Exploring Microsoft Fabric: Revolutionizing Data Integration and Analytics

In this digital era, managing and analyzing data has become a crucial factor in deciding the success of businesses. Microsoft is leading this transformation with Microsoft Fabric, an advanced platform that unifies data integration, real-time analytics, and AI powered insights.  

In a recent update, Microsoft introduced One Lake, a centralized data repository that simplifies access and collaboration, addressing the increasing demand for scalable solutions. Recently, organizations have been leaning heavily on AI tools to make the right decisions.  

Fabric’s ability to smoothly connect tools like Power BI, Azure Synapse, and Data Factory makes it a game changer. This read explores the innovative features and trends defining Microsoft Fabric’s role in the future of data management. 

What is Microsoft Fabric?

Microsoft Fabric is a unified analytics platform designed to provide businesses with a complete solution for data integration, analysis, and insights. Combining the powerful capabilities of Azure Data Factory and Azure Synapse Analytics, it enables organizations to utilize the potential of their data smoothly.   

A notable feature of Microsoft Fabric is its easy integration with other Microsoft tools and services, offering a personalized and cohesive solution for varied business needs. It serves as a robust data foundation with role specific tools, AI functionalities, and an open environment for analytics.  

Additionally, the platform enhances cost efficiency by optimizing resource management, allowing organizations to modernize their analytics processes effectively. With Microsoft Fabric, businesses can develop, deploy, and manage applications and services while adapting to the latest advancements in artificial intelligence and analytics.  

Key Components of Microsoft Fabric

Microsoft Fabric is built on seven core workloads, each designed to address specific needs within the data analytics and business intelligence ecosystem. These workloads work together to provide a unified platform simplifying data management. 

Synapse Data Engineering: This workload focuses on data engineering tasks, offering features like Spark authoring, live pools for instant startup, and collaborative capabilities to modernize data processing workflows. 

Synapse Data Science: A complete solution for data scientists, this workload covers the entire data science workflow, including model training, deployment, and management, with collaborative tools for team efforts. 

Synapse Data Warehousing: This workload integrates data lakes and data warehouses, offering industry leading SQL performance on open data formats. It provides a united lakehouse for optimized storage and analytics. 

Synapse Real Time Analytics: Enabling real time analysis of large semi-structured data, this workload processes data from IoT devices, telemetry, and logs, offering high performance and low latency. 

Power BI in Fabric: This component integrates Power BI’s visualization and AI analytics, allowing business analysts and end users to extract actionable insights and make data-driven decisions. 

Data Activator: It is a no-code solution for real time detection and monitoring. Data Activator allows businesses to identify patterns in data and trigger notifications and actions based on those insights.   

Benefits of Microsoft Fabric

 Centralizing Data with Ease   

Microsoft Fabric establishes a centralized data foundation, enabling organizations to integrate and manage various data sources effortlessly. This unified approach consolidates data from various systems, databases, and applications, creating a single, original source. It gives businesses a holistic view of their data, enabling efficient decision-making and modernizing data-driven operations.   

Tools Designed for Every Role   

Microsoft Fabric offers a set of tools personalized to specific user roles, enhancing productivity and simplifying workflows. Whether you are a developer, administrator, data scientist, or business analyst, the platform provides the tools you need to perform tasks efficiently. These role-specific features ensure users can focus on their responsibilities without unnecessary complexity.   

AI at the Core of Innovation   

Harnessing artificial intelligence, Microsoft Fabric allows users to have advanced AI-driven functionalities. From natural language processing to machine learning algorithms and predictive analytics, the platform integrates advanced AI features to extract deeper insights, automate repetitive tasks, and enable smarter decision making.   

Flexibility with Governance   

Microsoft Fabric supports an open and governed framework, accommodating various programming languages, tools, and frameworks. This flexibility allows developers to work with their preferred technologies while maintaining robust governance for security, compliance, and data privacy. The platform ensures organizations can innovate without compromising on critical regulatory requirements.   

Optimizing Costs Efficiently    

With a strong focus on resource optimization, Microsoft Fabric provides advanced cost management capabilities. It includes resource monitoring, usage analytics, and flexible scalability options, helping organizations control expenses while scaling infrastructure and applications as needed. This ensures cost-effective operations without sacrificing performance. 

The Integration of Power Apps, Power Automate, and Microsoft Fabric   

Microsoft’s ecosystem brings together powerful tools like Power Apps, Power Automate, and Microsoft Fabric to create a smooth and efficient workflow.   

Power Apps – Power Apps enable users to develop custom applications with minimal coding knowledge. By simplifying app creation, it allows users of all skill levels to craft solutions personalized to their unique business requirements.   

Power Automate – Power Automate enhances this ecosystem by offering tools to automate workflows and business operations. It helps reduce manual tasks and enables real-time responses to specific events, boosting operational efficiency.   

Microsoft Fabric – Microsoft Fabric, meanwhile, serves as an extensive analytics platform that enriches the capabilities of Power Apps and Power Automate. By centralizing data and integrating it with tools like SQL, Spark, and dataflows, it provides actionable insights to drive smarter business decisions within the Microsoft ecosystem.   

The relationship between Power Apps, Power Automate, and Microsoft Fabric is deeply interconnected, forming a symbiotic ecosystem. Power Apps and Power Automate benefit from the powerful analytics and insights provided by Microsoft Fabric, which relies on the data generated and managed within these platforms.  

This interdependence creates a modern approach, eliminating the need for traditional ETL (Extract, Transform, Load) processes. With this no-ETL framework, data can move smoothly across services, simplifying workflows and enabling real-time integration.  

This interaction allows organizations to utilize the full potential of their data, ensuring efficient collaboration between custom app development, automated workflows, and advanced analytics, all within the unified Microsoft ecosystem. 

Wrapping up  

With Microsoft Fabric, you no longer need to rely on multiple systems for your analytics tasks. When one task has unused capacity, Microsoft Fabric can smoothly allocate it to other tasks, ensuring that no power is wasted. This dynamic resource management significantly reduces costs while maximizing the performance and utility of your computing infrastructure. Microsoft Fabric offers a smarter way to handle data and analytics across your organization. 

bysira4

Benefits of Implementing Adobe Analytics for Your Business

Adobe Analytics is an enterprise solution known for its ability to harvest insights from every aspect of the customer journey. Unlike its well-known competitor, Google Analytics 360, there is no free version of Adobe Analytics. The application is used by larger enterprises that want to track every aspect of the customer journey, both online and offline.

These days a business’s website isn’t the only place where customers interact. They may engage with you using a mobile device, wearable tech, social media, a call center, digital assistants and surveys. They may also make a purchase in-person at brick-and-mortar store, access streaming media (OTT), use products with sensors that perform a function and connect to the Internet, called the Internet of Things (IoT). What’s a business to do to make sense of all of this data and gather the insights needed to really propel a business forward?

While most people think of Google Analytics to capture and analyze data, there are some important reasons they might choose the Adobe Experience Cloud solution instead.

What Google Analytics 360 and Adobe Analytics Have in Common?

Both Google Analytics 360 Suite and Adobe Analytics are designed for large companies that are ready to gather important business intelligence from the data they collect. Both enterprise analytics software packages have features in common:

  • Both integrate with their own proprietary marketing stack of applications: Google Marketing Platform and Adobe Experience Cloud
  • Both solutions are complex to setup, maintain and use. They require specific expertise to make use of all their capabilities.
  • Both measure website traffic and channels that bring online traffic.
  • Both have the ability to build reports.
  • Both are paid solutions.

What Are the Benefits of Using Adobe Analytics?

Adobe Analytics provides a more comprehensive way to track and analyze complex customer journeys and makes it possible to integrate your existing customer database for analysis. One data expert believes that it is the superior analytics platform for businesses that are ready to go beyond web reporting.

Adobe Analytics provides these four main benefits:

  • Website Analytics – Go beyond traffic to learn not only who is visiting your website but why they are there and what content they are looking for. Gather greater insights by looking at your website data alongside other channels to create a fuller picture.
  • Marketing Analytics – Omnichannel marketing requires the creation of customer journeys, not just measuring individual channels. This will give you a 360 view of your customers, so you can analyze how they react across the entire sales funnel.
  • Attribution – Find out which online and offline actions affect conversion throughout the customer journey. These insights give you the ability to track the value of every interaction.
  • Predictive Analytics – Artificial intelligence (AI) and machine learning helps spot anomalies and opportunities that can be acted on in real time. These tools help data experts and marketers find the insights they can use immediately.

Which Adobe Experience Cloud Products Are Commonly Used with Adobe Analytics?

Adobe Experience Cloud has a full marketing stack of products that seamless integrate to expand your capabilities. Here’s an overview of the most common applications:

  • Adobe Target – Gives you the ability to optimize and test every experience and apply AI-powered automation.
  • Adobe Experience Manager – This suite of apps combines the management of content and digital assets in one place.
  • Adobe Advertising Cloud – Unify and automate advertising in one place.
  • Adobe Campaign – Track customer journeys and deliver dynamic campaigns through multi-channels (email, mobile, etc.)
  • Adobe Audience Manager – This data management platform helps you segment and understand your customers.

Why Does My Enterprise Need Adobe Analytics?

 In a nutshell, Adobe Analytics can transform your business, giving the insights you need to better understand your customers and respond to them in real time.

In a nutshell, Adobe Analytic excels at helping large enterprises

  • Accommodate complex customer journeys
  • Access raw, unsampled data for greater accuracy
  • Make closed-loop analytics possible
  • Customize dashboards and reports for comprehensive analysis
  • Apply machine learning and intelligence technology (Adobe Sensei) to surface insights faster

Comprehensive Analytics for the Modern Enterprise

The largest companies choose Adobe Analytics to dig into their data to make the business decisions that lead to a long-term return on investment. This analytics platform is a superior choice for companies that have laid the groundwork for data-driven operations and are ready for true digital transformation. Not sure whether Google Analytics 360 or Adobe Analytics is best for you? Contact us today to start a conversation.

bysira4

Unlocking Business Growth with Google Analytics 360: Harnessing Data and Insights for Success

Businesses grow proportionally to their ability act on insights received from their data and analytics team. Google Analytics 360 is one of the most popular tools that large companies or enterprises use to gather data and use it to understand their customers, predict their behavior and drive results.

Google Analytics 360 vs Free

Google Analytics 360(formerly known as Google 360 Premium) is the paid version of the software. Large companies use Google 360 to measure trends, better understand the customer journey and use their data in ways that bolster return on investment.

Besides advanced analytics reporting, Google Analytics 360 differs from the free version in a variety of ways:

  • Dedicated service and technical support
  • Guaranteed data freshness
  • Customizable funnel reporting
  • Attribution modeling
  • Access to unsampled reports
  • Higher limits for data collection
  • Seamless integrations to Google BigQuery, Saleforce Marketing Cloudand others

The pricing for the enterprise edition is based on hit volume and requires a call with the Google sales team. Alternately, you can purchase it through a Google Marketing Platform Sales Partner.

How Does Google Analytics 360 Help?

 Google Analytics 360 is designed to help large companies to make sense of a large quantities of data so they can better understand their customers and what they need. Whether a customer interacts from an app or makes an online purchase, Google Analytics 360 can help you track the entire customer journey from start to finish.

Understanding how customers interact with your sites and apps makes it easier to measure trends and predict future customer behavior.

You can use these insights to improve your return on investment, optimizing your marketing performance overall. You use information you learn to create a more personalized experience and reach difference audiences to nudge them further along the marketing funnel.

You can also learn more about customer interests which you can deploy to optimize search and content marketing.

Greater insights about what is working well and not working well means you can quickly pivot to take advantage of opportunities, trends and ideas to streamline your business as they emerge.

In short, Google Analytics 360 turns your digital data into business intelligence.

What Components Are Part of the Google Marketing Platform?

 Google Analytics 360 integrates analytics and advertising data on a single marketing platform. The enterprise edition of Google Analytics 360 works seamlessly with the following modules:

Google Analytics 360 also integrates with other Google products and partner products. An integration with Google BigQuerygives even more flexibility to combine and analyze many different sources of data for further insights.

Data and Analytics for the Business Growth

Are you ready to deploy Google Analytics 360 for your business and have questions about what the next step might be? SiRA Consulting can partner with your team to deploy Google Analytics 360 and help you determine a smart strategy to accelerate your business. Contact us to start a conversation today.

bysira4

Why Having a Data and Analytics Strategy is Critical for Your Business

Now more than ever, our world is being driven by data and analytics, leading to the rise of a data-driven economy. Gartner predicts, “By 2022, 90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.” Indeed growing a corporation’s data and analytics competency is how modern businesses are finding success with digital transformation.

What Is Big Data?

 Big Data is a term describing all the many sources of data that a corporation, organization or business may have access to. Data can be gathered internally, such as recording sales and financial data, social media sentiment, online interactions, and from research and development. External data also can be accessed or purchased to give a more complete picture to inform your decisionmaking. Data by itself isn’t an asset until you have a solid plan and strategy that lines up with your business goals. A strategy defines (1) who is working on your strategy and will be working with the data, (2) what processes and decision making you will use, and  (3) the technology to make actionable insights possible. The following are elements to consider as you develop a robust data and analytics strategy that will give you a road map long into the future.

Business Goals

Begin with the end in mind. Determine first what your business goals are and what questions you need to answer to reach those goals. Do you need a way to make innovation faster, comply with regulations, decrease costs, connect more authentically customers or identify new sales opportunities? Look at the Key Performance Indicators (KPIs) you are using now throughout the organization to inform your discussions. These important conversations will help you get laser-focused on what data you will be able to gather to give you the business intelligence you need to move ahead.

Data Sources

Data can be structured or unstructured and come from both internal and external sources. You need to know where the data comes from, how it is gathered and what regulations you will need to abide by to keep it private and secure. An effective data governance policy will ensure the integrity of data and make sure it is not mishandled.

Data Storage and Infrastructure

Large quantities of data presents challenges for storing and analysis. What technology infrastructure will you need to store and process the data so you can gather the insights you need? Many companies use the cloud as a cost-effective and secure way to store data. Raw data can be stored in a data lake until is ready to be processed or accessed by a data scientist. Data warehouses, on the other hand, are set up to process data so it can be used for advanced analysis so it can act as a “single source of truth” to guide decision making. Some companies may choose one or the other, or even both! Data warehouse cloud solutions include Google BigQuery, Microsoft Azure, Snowflake, and Amazon RedShift. Cloud solutions for data lakes include Data Bricks, Amazon Web Services, Google Cloud Platform. Microsoft Azure and Snowflake.

Insights and Dashboards

Once you have your data set up, the next step is turning the data into insights. Determine what dashboards will you need and who in the organization will be using them to make decisions. Having the right level of detail for each audience who will be using these dashboards is important. At this level, you can spot efficiencies in the supply chain, leverage advertising and sales information, and better understand your customers and what they are wanting or don’t even know that they need yet. As your analytics game advances you’ll grow from not only understanding what is happening and why but also making better predictions for the future.

People and Process

As you move through this strategy process, you will need to take special care toward incorporating data-based decision making throughout your organization. You may need to hire employees with new skills or outsource to a specialized team on site or offshore. As your plan evolves, you may need to plan for training and incentives for employees to learn how to effectively and efficiently use these insights and to adopt new internal processes and operations. Be sure your plan includes a budget and considers what competing projects might affect the timeline for getting started.

Business Intelligence for the Modern Age

Harnessing and convertingdata into actionable business intelligence you can use to transform your business requires special expertise. But digital transformation is all but impossible without it. We live and breathe data, and can help you create a data and analytics strategy to propel your organization forward. Contact us to start a conversation today.