June 22, 2022 Easing Supply Chain Concerns with Optimized WiFi

WiFi automation platforms simplify real-time & long-term WiFi network optimization, ensuring all businesses have networks they need.

By Roger Sands, CEO and Co-founder of Wyebot, Inc.

If you turned off the WiFi in your manufacturing facilities and warehouses, what business processes would still continue? What drop in efficiency would you experience?

It doesn’t take an industry expert to know that the situation would be, at best, a serious headache. At its worst, facilities could be looking at a complete halt to all fulfillment and delivery processes.

WiFi networks are mission critical to business success and that includes easing supply chain concerns. This makes setting up and maintaining optimized networks a number one priority. To do this while saving time and money, use an AI-based automation solution.

How does AI-based automation help?

These solutions, like Wyebot’s Wireless Intelligence Platform™, work around the clock, analyzing all WiFi network activity, and then automatically delivering proactive alerts and actionable insights to IT teams. In effect, they become the eyes and ears of an IT department, only these eyes and ears can:

• Analyze thousands of data packets a second
• Work 24/7, even when no one else can be onsite
• Automatically identify root cause for performance issues to reduce the Mean-Time-to-Resolution (MTTR)
• Proactively alert IT to issues, often before end users are affected
• Cost-effectively scale to support facilities of all sizes

They ensure that a WiFi network is always reliable. They help prevent common issues – something like ineffective AP placements after warehouse shelves and pallets are moved around – as well as more complex issues, the kind of intermittent challenges that IT can spend weeks trying to resolve, such as seemingly unexplainable dropped connections.

This means that all devices and employees can depend on the WiFi to deliver the support necessary to protect business continuity. This includes the means to:

• Improve inventory management
• Make real-time improvements to processes and equipment
• Track goods and services as they move along the supply chain

Here’s how to use these solutions to optimize your network.

First, target actionable resolutions

The goal of WiFi automation solutions is to restore time and energy to IT teams while safeguarding and improving business continuity. To do this, these solutions should proactively deliver actionable resolutions. Here’s why:

• Proactive: proactive, automatic solutions are better than reactive, manual processes because they deliver alerts and insights in real-time, allowing IT to start resolving issues as soon as they occur, rather than requiring teams to wait for end users to submit problem tickets, and then wait again for intermittent issues to recur before data can be gathered and analyzed.
• Actionable resolutions: these analytics are useful and meaningful, giving IT everything they need to jump right to resolutions, rather than spending valuable time identifying root causes and determining possible solutions.

IT teams no longer have to wait for problems to find them. They can go on the offensive, resolving issues in real-time and minimizing downtime.

All teams are familiar with situations where a small problem went unnoticed thanks to the resilience of WiFi networks. These networks are designed to keep operations running as long as they aren’t overly taxed. When peak times arrive however, issues rear their ugly heads. Working with proactive, actionable alerts and resolutions significantly minimizes these network surprises and improves the end user experience.

Second, gather end-user quality metrics

A network is only as good as its employees think it is. To gain the best insights and determine if your network is meeting all expectations, you need end user quality metrics.

To get them, work with an automation solution that connects to the network as an end user device to run network tests. Tests should run on a continuous basis for the most useful analytics, and results should be automatically reported.

These metrics help administrators determine what, if any, changes are needed in regards to the technology being used and also the overall network design.

Third, future-proof with historical analytics

Historical wireless traces are an invaluable part of the optimization process. They deliver insight into long-term performance trends, allowing administrators to make budget friendly, personalized upgrade/update plans.

Use them to answer questions such as:

• Which specific APs need to be replaced?
• Is the network nearing capacity?
• Did last month’s, or last year’s, upgrades improve performance as expected?
• How has client distribution changed?
• How has the noise level changed?

Minimize concerns with simplified optimization

WiFi network ecosystems are dynamic and complex, and only growing more so every year. The secret though, is that optimizing them, protecting your brand’s reputation, improving the end user experience, and safeguarding business continuity, doesn’t have to be complicated at all.

It can be simple, fast, and cost-effective with the right AI-based WiFi automation platform. Make this your next technology adoption and set yourself up for long-lasting success.

Roger Sands is a co-Founder and CEO of Wyebot, Inc. Roger has 17 years of executive management positions in successful networking startups and Fortune 500 companies. Prior to  Wyebot, Roger was the Business Line Manager for Hewlett-Packard’s WW WLAN business growing it from #6 to #2 market share. Roger joined HP via the acquisition of Colubris Networks, a wireless startup where he held a number of executive positions including co-CEO and was instrumental in the HP acquisition. Prior to Colubris, he was a GM at Accton Technology founding the enterprise wireless business and building it to #3 market share via 6 strategic partnerships. Roger also held senior management positions at 3com, USRobotics and Bytex Corporation. Roger holds a Masters and Bachelors in Electrical Engineering at Northeastern University.

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