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The Role of AI Network Analytics in Strategic Decision Making


Strong strategic decisions require the decision maker to accurately predict future trends, challenges, and needs. This requires data-driven intelligence about past, present, and future industry performance and company performance. Decision makers must both know what they know and also know what they don’t know. The more they can fine-tune both elements, the better their strategic plans.  

 

So much of the data that decision makers depend on for strategic planning is in some way connected to the network. This is why leaders who integrate AI network analytics are better equipped to outperform competitors, reduce costs, and grow market share.

 

We’ll explain why.

 

The Growing Complexity of Strategic Decision Making

First, a breakdown of the four most significant challenges for today’s decision makers:

  1. Data Overload
    With thousands of connected devices at every worksite, data is everywhere. Enterprises are inundated with it. The problem isn’t getting the data, it’s making sense of it. Decision makers need intelligible insights, not data overload.
  2. Rapid Market Shifts
    With a global, interconnected market, shifts can happen rapidly and be fairly volatile. Everything from weather to geopolitical relations can affect the market. Executives must be able to respond to these shifts quickly – and ideally, responses should be strategic, not reactionary.
  3. More Reactionary Audiences
    Speaking of reactionary, today’s audiences – internal and external – react to events faster than ever before. Enterprises must be able to predict responses to various events and respond in a way that maintains positive relationships with all audiences: board, staff, partners, customers, press, etc.
  4. Hybrid Workplaces
    Strategic planning must cover all workplaces. In today’s world, this includes everything from offices, homes, planes, and coffeeshops, to warehouses and remote sites. Decision makers need actionable information on the current and future needs of employees in all of these locations.

How AI Network Analytics Support (Almost) Foolproof Decision Making

Now that we know the challenges, we can talk about how AI network analytics meet those needs and why they are a critical competitive asset. 

  1. At the Enterprise Level
    Networks are the backbone of every business.They must be reliable, future-proofed, and optimal. Without a strongly performing network, productivity is next to impossible. AI network analytics solutions proactively and automatically identify, troubleshoot, and mitigate network issues. They deliver the insights needed to keep networks – and all business processes – running optimally now and into the future.
  2. At the User Level
    Enterprises need to know the user experience of the network. Are certain applications lagging? Is certain software going unused because it doesn’t meet user needs? Is there a workflow that could be optimized? AI network analytics solutions analyze the network at the user level and deliver digital experience metrics so decision makers can upgrade networks to meet their specific users’ needs.
  3. At the Device Level
    Enterprises depend on IoT and other connected devices to analyze and optimize workflows, and deliver strategic insights. If these devices aren’t working properly, the necessary analytics cannot be delivered. AI solutions will analyze the performance of all connected devices and alert IT if there are any problems. Problems can be resolved quickly and devices can get back to work, delivering the insights that enterprises depend upon for operational superiority.

The Competitive Advantage of AI Network Analytics

  1. Accuracy
    Intelligent analytics are more accurate and less biased than user opinions. When enterprises use AI solutions to analyze all the data on hand, they are provided with more accurate, quantifiable insights.
  2. Scalability
    The amount of data available to enterprises is only going to increase. Decision makers need solutions that can scale with the business, no matter how fast growth occurs. AI network analytics solutions will continue to analyze performance and behavior, and provide expert-level insights effortlessly, every step of the way.
  3. Comprehension
    Maintaining an optimal network ecosystem that meets a company’s unique strategic goals requires detailed knowledge about the past and present, as well as predictions for the future
  • Past: Some AI analytics solutions will automatically analyze historical data and identify long-term performance and behavior trends not available with real-time only analysis.
  • Present: These solutions analyze networks, systems, connected devices, etc. and deliver actionable insights into performance and behavior in real-time. This allows enterprises to more quickly determine if plans they’ve implemented are producing the desired results.
  • Future: Solutions learn how to predict likely outcomes based on the extremely large datasets they analyze day in and day out. They allow enterprises to anticipate user needs and potential issues.

Real-World Results from Using AI Network Analytics

  1. Optimized Operations
    These solutions both pinpoint any business areas that require immediate attention and identify possible future issues. Enterprises are able to implement resolutions both quickly and proactively to optimize operations in the long-term.
  2. Improved Forecasting
    Working with technologies that predict market fluctuations and potential issues like supply chain disruptions and adverse weather conditions? AI network analytics solutions ensure those technologies are working as needed so that you have access to the intelligence you need, when you need it.
  3. Deeper User Insights
    Providing a positive digital experience is necessary to maintain a good brand reputation. Whether internally or externally, a company’s digital services must exceed expectations. Keep your network and all connected devices, applications, platforms, and software attuned to your audiences’ specific needs with AI network analytics.
  4. Improved Risk Mitigation
    AI network analytics both identify network threats – such as unauthorized access points (APs) and open network ports – and promote healthy networks to support advanced crisis prediction technologies. The end result? Improved risk mitigation.
  5. Superior Cost Efficiency
    The above benefits deliver protected business continuity, improved operational efficiency, and streamlined strategic planning. This reduces overall enterprise costs while boosting profits.

Strategic Decision Making: The AI Way

If you want actionable insights, you need intelligent-powered analytics solutions. Cast out the noise, eliminate network mysteries, and give your decision makers the answers they need to promote long-term strategic growth.

 

Ask us about how the Wireless Intelligence Platform™ and DEX Agent keep companies performing stronger than ever.

 

Wyebot is the leader in AI-driven WiFi Automation. Our sensor, cloud, and client device technologies eliminate wired and WiFi network issues and improve the digital experience for every user, independent of location. Our award-winning, first-to-market, innovative solutions are changing people’s lives in the enterprise, healthcare, manufacturing + warehousing, MSP, retail and education industries.

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