Our Guide to Achieving the Right Network Solution with SD-WAN and SASE

Richard Brown


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Q&A: What you need to know about SD-WAN & SASE, with Richard Brown


Richard Brown, former COO of Cambridge MC, chaired a panel at the WAN SUMMIT in London earlier this year.


Here he gives a Q&A about the outlook for SD-WAN at the end of 2021 and farther ahead into 2022. He explains how SD-WAN has moved past the hype and is now developing further in anticipation of the changes brought by 5G.


Richard also discusses how SASE will integrate with SD-WAN to create next-gen security and user experience.


Abstract ripples in concentric circles

What is SD-WAN and how does it work?


A Software-defined Wide Area Network (SD-WAN) is an overlay technology that allows enterprises to use any combination of transport services, including DIA, LTE, broadband services, as well as MPLS. 


SD-WAN simplifies management of a WAN by decoupling the hardware from its control mechanism. This concept is similar to how software-defined networking implements virtual technology to improve data centre management.

 

Gartner has defined an SD-WAN as having four characteristics:

 

  • The ability to support multiple connection types
  • Dynamic path selection, for load sharing and resilience
  • A simple interface that can be configured
  • The ability to support VPNs, and 3rd party services, such as WAN optimisation controls, firewalls and gateways 


SD-WAN is a key enabler to allow enterprises to connect users to applications via an efficient and flexible system, offering increased performance and Quality of Experience (QoE).


Infographic showing SD-WAN structure

What are the benefits of SD-WAN?


SD-WAN uses a centralised control function to direct traffic across the WAN with intelligent programming. This delivers much greater application performance and efficiency, significantly improving Quality of Experience (QoE) for the user. Other benefits include productivity, agility and reduced costs. 

 

Traditional WAN architecture was never designed to support cloud applications and Software-as-a-Service (SaaS). Typically, in scenarios where a router-centric architecture is used with cloud applications, all the data is backhauled to a hub or branch data centre where centralised firewalls provide protection. This can result in poor QoE due to high latency and restricted bandwidth, particularly where expensive MPLS is used as the backhaul.

 

The SD-WAN model is designed to fully support a hybrid environment, with applications hosted in on-premise data centres, public or private clouds and delivered via SaaS services such as Office 365 and SalesForce, with direct and secure routing of user traffic from their location.


Has SD-WAN moved past the hype phase?


SD-WAN has finally moved through the hype phase. In one recent survey, 50% had either deployed or are in the process of piloting and rolling out SD-WAN.

 

As recently as three years ago, SD-WAN was being touted as the solution to drastically reduce the cost of the underlay network. The concept was to harness the error correction and load sharing capabilities of the overlay to drive out enterprise grade performance over multiple cheap broadband connections.

 

It is striking how much understanding and thinking has moved on. 

 

The anticipated move by enterprises away from expensive single vendor MPLS networks and traditional managed router networks is certainly happening. However, the driving factors are often more about keeping up with demand than cost savings. 

 

The reliance on cloud-based services in all areas of business has driven network traffic patterns from traditional hub (data centres) and spoke (users and sites) to user direct to the cloud. 

 

Users need high quality connectivity across the internet to digital applications and public cloud services. And they need ever more bandwidth. The pandemic has also accelerated SD-WAN adoption across most sectors. Despite a high baseline set in 2020, figures show that SD-WAN continued to grow at a stellar rate in 2021. 

 

The move to remote working and the continuation of hybrid working models has created a sustained demand for deployments that provide a fast and stable network for remote collaboration among teams. Vendors are constantly updating their packages; finding new ways to meet the challenges set by IT departments. 

Complex glowing screen of numbers and flowcharts

What do I need to know about my network underlay?


It’s also become clear that underlay quality is still a factor to be considered. It is simply not enough to say: ‘it’s the internet, what do you expect?’ Internet connectivity must perform consistently to a level that meets business needs.

 

It’s not enough to solely rely on clever programming within the SD-WAN overlay to overcome bad internet connections. This does help, particularly when you hit temporary patches of poor performance, but nevertheless careful consideration is required to select the internet providers that can deliver the performance you need. With huge growth in streaming, and technology that requires real-time output, networks must also deliver on latency. 

 

Understanding where internet providers peer to other providers to route your user/site traffic to mission critical internet destinations is vital knowledge, particularly internationally. It’s common to find your traffic is actually routing through multiple countries simply because you chose an ISP that did not have peering locally.


What is SASE and does it replace SD-WAN?


Secure Access Service Edge (SASE) is a security model that was initially proposed in a report by Gartner in August 2019. 

 

Essentially, SASE combines SD-WAN and security services such as CASB (Cloud Access Security Broker), FWaaS (Firewall-as-a-Service) and Zero Trust, delivering them together as a single cloud service. 

 

Security policies enforced on user sessions are tailored to set requirements based on four factors:

 

  • The identity of the connection
  • Context – the health and behaviour of the device and sensitivity of the resource being accessed
  • Security and compliance policies
  • An ongoing assessment of risk in each session


The ‘edge’ part of SASE is usually delivered through PoPs or vendor data centres close to the endpoints —the data centres, users, and devices. In some cases, SASE vendors own the PoPs, while sometimes they use a third-party supplier. The philosophy of SASE is to bring security closer to the user, allowing for authentication and then direct access to resources to reduce latency. 


In short, no SASE does not replace SD-WAN. It is more like the peanut butter to SD-WAN's jam.


It is a security extension that will offer many other advantages and help realise the future benefits of 5G and Edge computing. SASE is an evolution of SD-WAN but it does not fundamentally replace or change the infrastructure. It is, at this stage, more a philosophy and a model to improve security protocols in an SD-WAN overlay.

Infographic showing SD-WAN overlay

What are the benefits to SASE?


Gartner predicts that 40% of enterprises will have SASE adoption plans by 2024. 

 

Because it is a single service, SASE reduces complexity and cost. Enterprises deal with fewer vendors, and the amount of hardware required in branch locations declines.


IT departments can set policies via cloud-based management platforms, and the protocols are enforced at distributed PoPs close to end-users.


Users have the same access experience regardless of what resources they need and where they are located. SASE simplifies the authentication process by applying appropriate security policies depending on the nature of the resources requested.


SASE also supports zero-trust networking, which bases access on user, device and application, not location and IP address.


Are there disadvantages to SASE?


Unfortunately, getting your underlay right is not as straightforward as we might hope. SASE can also cause performance issues.


You might have great connectivity from an office in Rio de Janeiro to a public cloud service in Sao Paulo over the internet, but if you have to send your traffic to a SASE provider in Miami first, you are unlikely to get the performance you need. 

 

Another disadvantage is a lack of standard or official criteria for SASE. This means some vendors may offer services that do not meet your requirements or the expectations of the model.

 

We recommend that enterprises take several key things into account:

 

  • Analyse uptime and availability SLAs, along with the breadth of PoPs for connectivity
  • Assess network and network security capabilities. SASE platforms do not excel at all network functions and services collectively, so evaluate their strengths and weaknesses. For example, some may excel at SD-WAN and traffic optimization,  while others are more focused on CASB or VPN replacement.

 

There are other issues that are not addressed in the Gartner report. This creates grey areas that will need further research and analysis:

 

  • Scalability
  • Latency
  • Meeting other requirements: redundancy, reliability, MTTR, customer service
  • New metrics for measuring the effectiveness of new parameters in a new environment
  • Lack of any official description/standard


How do I choose the right SD-WAN overlay?


SD-WAN overlays are being managed in a variety of ways from internally managed through to buying in a fully managed service. However, as discussed at the WAN summit, ‘vanilla’ managed SD-WAN services are likely to fall short. 

 

In our experience, enterprises were often disenchanted with their traditional managed router service from suppliers, as the race to the bottom on costs often led to suppliers offering only simple ‘up/down’ monitoring of links and fault handing and little more. At the same time enterprise expected a lot more from a ‘managed service’, such as proactive performance monitoring and intervention. 

 

SD-WAN takes both expectations and requirements to a whole new level, because the network is interacting with applications, not just acting as a pipe. While early SD-WAN adopters tended to manage their networks in-house already, and carried on doing so with SD-WAN, others have moved towards a co-managed model where there is a division of responsibility between a supplier with the technical know-how and operational capability to handle faults, and the customer with deeper understanding of their whole ecosystem. 

 

As Network-as-a-Service matures, we will see operators and service integrators that integrate and operate with enterprise clients closely enough to move the boundaries again; so that enterprise takes less of the load. 


Research suggests that if enterprises consider existing skillsets, vendors, products and timing of hardware refresh cycles as migration factors, they will reduce their SASE adoption time by half.


AI operations is likely to be the next paradigm. Automation and AI will have a vital part to play in the fast triage of issues and self-heal in the network and is likely to be an important component in bridging the gap between customer expectations of a managed SD-WAN service and affordability. 

 

Despite the investment required to implement SD-WAN and SASE, by both suppliers and enterprise clients, the eventual benefits of improved performance and reduced costs inevitably leads to a convergence between network and security. Remote working and the continuation of hybrid working models has also given SD-WAN a boost 

 

It will be interesting to find out what the cloud giants, AWS, Microsoft and Google, offer as their own SASE recipe to fight off competition. This is an evolving market, and there will be a long list of hybrid models and integrations before the playing field levels out.

 

The growth of IoT and Edge computing will only increase the need for SaaS applications and cloud storage. To move away from on-premises architecture and security, the SASE model will need greater adoption; this way, end users and devices can gain secure access to all the resources they require with protection from security located close to them. Once users are authenticated, they have direct access to resources, which improves latency.

 

This convergence will mean enterprises need to consider how they adjust their organisational boundaries to reflect this new reality.


Will SD-WAN help prepare for 5G?


Banner showing 5G letters glowing neon

5G will emerge as another important underlay access service to sit under the SD-WAN overlay. Those that have adopted SD-WAN already are likely to find it easier to adopt this access technology that trying to plug 5G into a traditional router network, providing an important and cost effective network access method of particular use cases.


SASE and 5G also offer complimentary benefits —SASE being the best model to create security authentication at the network edge, rather than having direct traffic back to the core. SASE can offer automatic verification and authentication gateways between the user and the enterprise where they are located. It will allow endpoints to access private 5G network slices, authenticating users not only as they cross the enterprise boundary, but also according to rules and hierarchy as they access each specific application.


Early adoption of the SASE model and integrated services, paves the way for a secure 5G network and complete cloud security strategy in the future. With a security and network management platform combined with 5G flexibility and speed (particularly over the last-mile), companies will be prepared for the inevitable confluence of SD-WAN, SASE and 5G.


These future technologies make it an exciting time for SD-WAN. We are past the hype and now well on our way into full adoption. With the advent of SASE, Edge compute and 5G, there will be huge leaps forward for performance, in both bandwidth and latency. AI will also create decision-making at nodes, creating faster and more intelligent network routing.  


Find out about our SD-WAN, cloud & network transformation services


Building on decades of experience delivering network change, we have the skillset to deliver the complex network transformation programs necessary to prepare for agile change in rapid markets. 


We can transition your network from data centres to the cloud and hosting space such as Azure and AWS. As digital tools and data analytics become increasingly mission-critical, agile networks are required to underpin rapid movement in IT and business strategies. We help you make the right choices among the hype and the myriad options on offer.


Find out more about our SD-WAN and network architecture consultancy services


About Us


Cambridge Management Consulting (Cambridge MC) is an international consulting firm that helps companies of all sizes have a better impact on the world. Founded in Cambridge, UK, initially to help the start-up community, Cambridge MC has grown to over 200 consultants working on projects in 24 countries. Our capabilities focus on supporting the private and public sector with their people, process and digital technology challenges.


What makes Cambridge Management Consulting unique is that it doesn’t employ consultants – only senior executives with real industry or government experience and the skills to advise their clients from a place of true credibility. Our team strives to have a highly positive impact on all the organisations they serve. We are confident there is no business or enterprise that we cannot help transform for the better.


Cambridge Management Consulting has offices or legal entities in Cambridge, London, New York, Paris, Dubai, Singapore and Helsinki, with further expansion planned in future. 


Find out more about our digital transformation services and full list of capabilities

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by Darren Sheppard 4 December 2025
What is the Contract Lifecycle Management and Why does it Matter? The future success of your business depends on realising the value that’s captured in its contracts. From vendor agreements to employee documents, everywhere you look are commitments that need to be met for your business to succeed. The type of contract and the nature of goods or services it covers will determine what sort of management activities might be needed at each stage. How your company is organised will also determine which departments or individuals are responsible for what activities at each stage. Contract Lifecycle Management, from a buyer's perspective, is the process of defining and designing the actual activities needed in each stage for any specific contract, allocating ownership of the activities to individuals or groups, and monitoring the performance of those activities as the contract progresses through its lifecycle. The ultimate aim is to minimise surprises, ensure the contracted goods or services are delivered by the vendor in accordance with the contract, and realise the expected business benefits and value for money. The Problem of Redundant Spend in Contracts Despite the built-in imbalance of information favoring suppliers, companies still choose to oversee these vendors internally. However, many adopt a reactive, unstructured approach to supplier management and struggle to bridge the gap between contractual expectations and actual performance. Currently, where governance exists, it is often understaffed, with weak, missing, or poorly enforced processes. The focus is primarily on manual data collection, validation, and basic retrospective reporting of supplier performance, rather than on proactively managing risk, relationships, and overall performance. The amount of redundant spend in contracts can vary widely depending on the industry, the complexity of the contracts, and how rigorously they are managed. For further information on this, Cambridge MC’s case studies provide insights into typical ranges and common sources of redundant spend. As a general estimate, industry analysts often state that redundant spend can account for as much as 20% of total contract value. In some cases, especially in poorly managed contracts, this can be much higher. What is AI-driven Contract Management? Artificial Intelligence (AI) is redefining contract management, transforming a historically time-consuming and manual process into a streamlined, efficient, and intelligent operation. Traditionally, managing contracts required legal teams to navigate through extensive paperwork, drafting, reviewing, and monitoring agreements — a process prone to inefficiencies and human error. With the emergence of artificial intelligence, particularly generative AI and natural language processing (NLP), this area of operations is undergoing a paradigm shift. This step change is not without concerns however, as there are the inevitable risks of AI hallucinations, training data biases and the threat to jobs. AI-driven contract management solutions not only automate repetitive tasks but also uncover valuable insights locked up in contract data, improving compliance and reducing the risks that are often lost in reams paperwork and contract clauses. Put simply, AI can automate, analyse, and optimise every aspect of your contract lifecycle. From drafting and negotiation to approval, storage, and tracking, AI-powered platforms enhance precision and speed across these processes; in some cases reducing work that might take several days to minutes or hours. By discerning patterns and identifying key terms, conditions, and concepts within agreements, AI enables businesses to parse complex contracts with ease and efficiency. In theory, this empowers your legal and contract teams (rather than reducing them), allowing personnel to focus on high-level tasks such as strategy rather than minutiae. However, it is important to recognise that none of the solutions available in the marketplace today offer companies an integrated supplier management solution, combining a comprehensive software platform, capable of advanced analytics, with a managed service. Cambridge Management Consulting is one of only a few consultancies that offers fully integrated Contract Management as a Service (CMaaS). Benefits of Integrating AI into your Contract Lifecycle Management Cambridge MC’s Contract Management as a Service (CMaaS) 360-degree Visibility: Enable your business to gain 360-degree visibility into contracts and streamline the change management process. Real-time Data: Gain real-time performance data and granularly compare it against contractually obligated outcomes. More Control: Take control of your contracts and associated relationships with an integrated, centralised platform. Advanced meta data searches provide specific information on external risk elements, and qualitative and quantitative insights into performance. Reduces Costs: By automating manual processes, businesses can significantly reduce administrative costs associated with contract management. AI-based solutions eliminate inefficiencies in the contract lifecycle while minimising reliance on external legal counsel for routine tasks. Supplier Collaboration: Proactively drive supplier collaboration and take a data-driven approach towards managing relationships and governance process health. Enhanced Compliance: AI tools ensure that contracts adhere to internal policies and external regulations by flagging non-compliant clauses during the drafting or review stage. This proactive approach reduces the risk of costly disputes or penalties. Reduces Human Errors: In traditional contract management processes, human errors can lead to missed deadlines and hidden risks. AI-powered systems use natural language processing to identify inconsistencies or inaccuracies in contracts before they escalate into larger issues. Automates Repetitive Tasks: AI-powered tools automate time-consuming tasks such as drafting contracts, reviewing documents for errors, and extracting key terms. This frees up legal teams to focus on higher-value activities like strategic negotiations and risk assessment. We can accurately model and connect commercial information across end-to-end processes and execution systems. AI capabilities then derive and apply automated commercial intelligence (from thousands of commercial experts using those systems) to error-proof complex tasks such as searching for hidden contract risks, determining SLA calculations and performing invoice matching/approvals directly against best-in-class criteria. Contract management teams using AI tools reported an annual savings rate that is 37% higher than peers. Spending and tracking rebates, delivery terms and volume discounts can ensure that all of the savings negotiated in a sourcing cycle are based on our experience of managing complex contracts for a wide variety of customers. Our Contract Management as a Service, underpinned by AI software tooling, has already delivered tangible benefits and proven success. 8 Steps to Transition Your Organisation to AI Contract Management Implementing AI-driven contract management requires a thoughtful and structured approach to ensure seamless integration and long-term success. By following these key steps your organisation can avoid delays and costly setbacks. Step 1 Digitise Contracts and Centralise in the Cloud: Begin by converting all existing contracts into a digital format and storing them in a secure, centralised, cloud-based repository. This ensures contracts are accessible, organised, and easier to manage. A cloud-based system also facilitates real-time collaboration and allows AI to extract data from various file formats, such as PDFs and OCR-scanned images, with ease. Search for and retrieve contracts using a variety of advanced search features such as full text search, Boolean, regex, fuzzy, and more. Monitor upcoming renewal and expiration events with configurable alerts, notifications, and calendar entries. Streamline contract change management with robust version control and automatically refresh updated metadata and affected obligations. Step 2 Choose the Right AI-Powered Contract Management Software: Selecting the right software is a critical step in setting up your management system. Evaluate platforms based on their ability to meet your organisation’s unique contracting needs. Consider key factors such as data privacy and security, integration with existing systems, ease of implementation, and the accuracy of AI-generated outputs. A well-chosen platform will streamline workflows while ensuring compliance and scalability. Step 3 Understand How AI Analyses Contracts: To make the most of AI, it’s essential to understand how it processes contract data. AI systems use Natural Language Processing (NLP) to interpret and extract meaning from human-readable contract terms, while Machine Learning (ML) enables the system to continuously improve its accuracy through experience. These combined technologies allow AI to identify key clauses, conditions, and obligations, as well as extract critical data like dates, parties, and legal provisions. Training your team on these capabilities will help them to understand the system and diagnose inconsistencies. Step 4 Maintain Oversight and Validate AI Outputs: While AI can automate repetitive tasks and significantly reduce manual effort, human oversight is indispensable. Implement a thorough process for spot-checking AI-generated outputs to ensure accuracy, compliance, and alignment with organisational standards. Legal teams should review contracts processed by AI to verify the integrity of agreements and minimise risks. This collaborative approach between AI and human contract management expertise ensures confidence in the system. Step 5 Refine the Data Pool for Better Results: The quality of AI’s analysis depends heavily on the data it is trained on. Regularly refine and update your data pool by incorporating industry-relevant contract examples and removing errors or inconsistencies. A well-maintained data set enhances the precision of AI outputs, enabling the system to adapt to evolving business needs and legal standards. Step 6 Establish Frameworks for Ongoing AI Management: To ensure long-term success, set clear objectives and measurable goals for your AI contract management system. Define key performance indicators (KPIs) to track progress and prioritise features that align with your organisation’s specific requirements. Establish workflows and governance frameworks to guide the use of AI tools, ensuring consistency and accountability in contract management processes. Step 7 Train and Empower Your Teams: Equip your teams with the skills and knowledge they need to use AI tools effectively. Conduct hands-on training sessions to familiarise users with the platform’s features and functionalities. Create a feedback loop to gather insights from your team, allowing for continuous improvement of the system. Avoid change resistance by using change management methodologies, as this will foster trust in the technology and drive successful adoption. Step 8 Ensure Ethical and Secure Use of AI: Tools Promote transparency and integrity in the use of AI-driven contract management. Legal teams should have the ability to filter sensitive information, secure data within private cloud environments, and trace data back to its source when needed. By prioritising data security and ethical AI practices, organisations can build trust and mitigate potential risks. With the right tools, training, and oversight, AI can become a powerful ally in achieving operational excellence as well as reducing costs and risk. Overcoming the Technical & Human Challenges While the benefits are compelling, implementing AI in contract management comes with some unique challenges which need to be managed by your leadership and contract teams: Data Security Concerns: Uploading sensitive contracts to cloud-based platforms risks data breaches and phishing attacks. Integration Complexities: Incorporating AI tools into existing systems requires careful planning to avoid disruptions and downtime. Change Fatigue & Resistance: Training employees to use new technologies can be time-intensive and costly. There is a natural resistance to change, the dynamics of which are often overlooked and ignored, even though these risks are often a major cause of project failure. Reliance on Generic Models: Off-the-shelf AI models may not fully align with your needs without detailed customisation. To address these challenges, businesses should partner with experienced providers who specialise in delivering tailored AI-driven solutions for contract lifecycle management. Case Study 1: The CRM That Nobody Used A mid-sized company invests £50,000 in a cutting-edge Customer Relationship Management (CRM) system, hoping to streamline customer interactions, automate follow-ups, and boost sales performance. The leadership expects this software to increase efficiency and revenue. However, after six months: Sales teams continue using spreadsheets because they find the CRM complicated. Managers struggle to generate reports because the system wasn’t set up properly. Customer data is inconsistent, leading to missed opportunities. The Result: The software becomes an expensive shelf-ware — a wasted investment that adds no value because the employees never fully adopted it. Case Study 2: Using Contract Management Experts to Set Up, Customise and Provide Training If the previous company had invested in professional services alongside the software, the outcome would have been very different. A team of CMaaS experts would: Train employees to ensure adoption and confidence in using the system. Customise the software to fit business needs, eliminating frustrations. Provide ongoing support, so issues don’t lead to abandonment. Generate workflows and governance for upward communication and visibility of adherence. The Result: A fully customised CRM that significantly improves the Contract Management lifecycle, leading to: more efficient workflows, more time for the contract team to spend on higher value work, automated tasks and event notifications, and real-time analytics. With full utilisation and efficiency, the software delivers real ROI, making it a strategic investment instead of a sunk cost. Summary AI is reshaping the way organisations approach contract lifecycle management by automating processes, enhancing compliance, reducing risks, and improving visibility into contractual obligations. From data extraction to risk analysis, AI-powered tools are empowering legal teams with actionable insights while driving operational efficiency. However, successful implementation requires overcoming challenges such as data security concerns and integration complexities. By choosing the right solutions, tailored to their needs — and partnering with experts like Cambridge Management Consulting — businesses can overcome the challenges and unlock the full potential of AI-based contract management. A Summary of Key Benefits Manage the entire lifecycle of supplier management on a single integrated platform Stop value leakage: as much as 20% of Annual Contract Value (ACV) Reduce on-going governance and application support and maintenance expenses by up to 60% Deliver a higher level of service to your end-user community. Speed without compromise: accomplish more in less time with automation capabilities Smarter contracts allow you to leverage analytics while you negotiate Manage and reduce risk at every step of the contract lifecycle Up to 90% reduction in creating first drafts Reduction in CLM costs and extraction costs How we Can Help Cambridge Management Consulting stands at the forefront of delivering innovative AI-powered solutions for contract lifecycle management. With specialised teams in both AI and Contract Management, we are well-placed to design and manage your transition with minimal disruption to operations. We have already worked with many public and private organisations, during due diligence, deal negotiation, TSAs, and exit phases; rescuing millions in contract management issues. Use the contact form below to send your queries to Darren Sheppard , Senior Partner for Contract Management. Go to our Contract Management Service Page
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