Sandvine is a leading provider of network intelligence for network operators. At the heart of its solution stack is a data collection technology that enables it to ‘classify’ all network traffic in real-time and understand the most granular aspects of the voice, video, and data streams that traverse the network.
The company sees and captures real-time data from the network and organizes it into ‘subscriber aware correlations’ to illuminate the details of subscriber device, subscriber service utilization, and their mobility and network activity to characterize a true quality of experience (QoE).
As Sandvine’s technology sits ‘in-line’ in a network traffic flow, the company specializes in what it terms Active Network Intelligence, which takes its analytics offerings and turns them into ‘closed-loop’ actions on the network. Sandvine further takes this foundation of high definition correlated data and turns it into a portfolio of pre-packaged software use cases in order for its customers to benefit from solving high ROI-specific problems with short cycle times to deploy and turn up.
The company’s analytics data and use case portfolio covers five ‘save money and make money’ solution categories (Analytics, Network Optimization, Revenue Generation, Revenue Assurance, and Regulatory Compliance). These are represented to users in a single pane of glass with intuitive graphical dashboards and drill through workflows enabling unique perspectives that deliver end-to-end views of subscriber and service delivery across key applications like video, gaming, and social sharing for consumers.
A Visionary Leader
Lyn Cantor (or Lyndon Cantor) is the CEO of Sandvine, a merger of Procera (the company that he ran previously) and Sandvine (Procera’s biggest competitor in the Deep Packet Inspection (DPI) market). He has spent over 25 years of his career in the OSS space, where the foundation of ‘real-time data collection’ and understanding the patterns and behaviors within the data has been the critical building block to unlocking customer value.
Lyn’s vision for Sandvine has been to move the company from being a DPI technology business and an ‘intelligent data source’ for its customers whose value was unlocked by a professional services implementation model to a leader of the cloud-delivered software solutions that leverage ‘the best data on the planet’ with the ‘best pre-package use cases’ all controlled through an intuitive GUI. His team has done an excellent job of executing against this vision and they are well on the path of delivering against this vision and transforming Sandvine’s market segment.
Contributing to the Industry Benefits
There are two very specific contributions that Sandvine is making in the market that Lyn thinks delivers the biggest benefit to the industry. The first is the company’s investment in a machine learning-powered application classification engine that enables Sandvine to continue to classify traffic despite the increasing use of end-to-end encryption. Without application-layer visibility, operators do not know what QoE they are delivering to their users; Sandvine includes the QoE KPIs as part of that classification to ensure that investments in QoE are maximized. The second area of the company’s contribution is the focused use of machine learning on its application and QoE data to deliver tightly focused closed-loop use cases that can be deployed today. One example is Sandvine’s Automated WiFi QoE Analytics use case that enables operators to not only detect WiFi QoE issues in the home but also to recommend fixes to the issues. Another is Intent-Based Congestion Management, which enables operators to define the goals of network QoE based on business targets, and then have the network policies adapt in real-time to maximize the delivered QoE.
Analytics as a Foundational Value Proposition
Sandvine’s strength has always been in its ability to recognize traffic from its DPI heritage. The company is a leader in this market, and its Global Internet Phenomena Report is acknowledged as the authoritative source for internet trends for network operators and application providers. This strength is the foundation of its value offering to customers, as without that level of visibility, and most importantly, accuracy, decisions get made that do not reflect the actual state of networks or do not deliver the profitability needed to give a competitive market advantage to Sandvine’s customers.
Challenge to Bring Technology to the Forefront
According to Lyn, the biggest challenge was to make the transition from a technology company to a solutions company. He needed to make not only the internal team understand the shift, but also his customer base. Analytics couldn’t be just another offering in Sandvine’s portfolio, it had to be front and center in everything that the company does. As an acknowledgment of this, in 2019 Sandvine launched its Active Network Intelligence Portal, which took its unique data and optimized the workflow for its analytics data on a per-use case basis for all of its offerings. Lyn says, “This helped the company make the transition because as they say, ‘a picture is worth 1000 words!’ especially in the analytics market. If you cannot compellingly present your data, then the customer will not see value in it.”
Need to Maximize the Impacts of Innovation
Lyn tends to think of needing to start at the end and working backward… especially from a visual management perspective. Building and innovating today, for him, involves a lot more detailed UX / UI design at the front end, versus leaving it to a Product or Development team to figure out ‘organically.’
He said, “Ironically, I would say that innovative leaders need to use analytics in their everyday jobs to not only come up with innovations but also to ensure that the innovations can be operationalized. When you are trying to be a market maker, it requires a lot of attention to detail in terms of what you want customers to see and how you can best provide value through intelligent and simplified workflows. We learned through our transformation that if you miss the little details, you will not maximize the impact with your innovations.”
The second attribute that Lyn emphasized is to provide vision to the team and let them innovate within that vision. Sandvine’s automation team was given the mandate to find use cases within the data that it had, which resulted in innovations such as the WiFi QoE use case that took people by surprise and resulted in a huge value to customers. When the company describes that use case to customers, they are surprised that Sandvine can deliver what it promises, but when they see the results, they are convinced. This is solely due to the strength of the data and the innovative mind of the team that designed the solution.
Evaluating Through Customers’ Valuable Opinions
The key to innovating one’s product/solution in a way that appeals to target the audience, according to Lyn, is to listen to customers in order to find the intersection of the problems that are causing them the biggest challenges and the ways that the company can help them with its technology.
Innovation comes from hearing a problem that someone is struggling with, or even seeing something that they don’t understand yet as a problem, and being able to identify a path to help them. Sandvine has developed a DevOps model to work with customers in these type of situations to ensure that the company is not just developing solutions in a vacuum. This direct interaction has made Sandvine’s offerings better than if it had developed in its own labs because the company has real customer data and interaction on a daily basis as the solutions are hardened.
Enabling New Opportunities with Machine Learning
Lyn sees machine learning – correctly applied – enabling new opportunities to optimize networks for operators. In some situations, these analytics-driven use cases will save money, enabling operators to make their CAPEX more efficient, and in others they will make more money, resulting in a better ROI. He sees the most important factor in the analytics industry is getting the right data, not just more data. Many network operators struggle with analytics because they are using the wrong data, or simply have too much and do not know which data to start with.
Knowing Your Data is a Must
“Data is key. Knowing what you want to make from it is key. Making it packaged, repeatable, and scalable is key,” says Lyn. He advises emerging business leaders to be very engaged internally and hands-on in the design of every aspect of what the customer sees and how they will use and benefit from it. According to him, “you must make sure you have good, timely data that can feed your decision-making processes, and dig into it on a regular basis to ensure that it is giving you the complete picture of what is happening in your business.”
He further suggests for customers to make sure the data is delivering the outcomes that the company is promising – close the loops to validate its value. Leveraging a DevOps relationship model to unlock the power of iteration and a ‘fail fast but keep moving’ mentality is wise. GUIs, workflows, and data correlations are an evolving thing… the best outcomes surface after a lot of team and customer iterations and the mindset of continuous improvement.
For Lyn, analytics data has always been something one works to analyze, package, and present in compelling ways, then iterate continuously as the insights evolve. In his point of view, if people can find the right balance here and stay close to their customers’ feedback on each of their analytics use cases and their value from an ROI perspective, they will build long-term strategic relationships with customers that enable success. Lyn’s team is hard at work to do this for Sandvine’s customers every day. At last, he quotes, “Happy hunting and may all your data be insightful.”
Source: Analytics Insight