Digitization, Digitalization, & Digital Transformation: What's the Difference?

Digitization (dig-​i-ti-​za-tion) and digitalization (dig-​i-​tal-​i-za-tion) may sound similar and are often used interchangeably, but the reality is they are two separate concepts that accomplish unique goals. 

Digital aspects have become interwoven into the steady rhythm of our lives, so much so that we often don’t even realize it anymore. We can go for hours with only our smartphones and limited human interaction without batting an eye. 

Imagine a typical afternoon of running errands:

These scenarios all encompass digital transformation across numerous areas of business and various verticals.

Each digital touchpoint has a business behind it that is working to incorporate numerous digital aspects that contribute to transforming a process to be more ‘seamless’ to the end-user, whether through digitization or digitalization. Understanding these different versions of digital can quickly lead to confusing tongue-twisters. 

In this blog, we’ll break it all down and discuss ways digital transformation can help optimize your business processes and benefit the future of your enterprise as a whole.

Digitization

What is Digitization? 

According to Gartner, digitization is defined as “the process of changing from analog to digital form, also known as digital enablement. Said another way, digitization takes an analog process and changes it to a digital form without any different-in-kind changes to the process itself.”

Digitizing is when data is converted to a digital format but the data itself does not change. Digitization can have notes of nostalgia since many of the examples hearken back to past decades. Digitization could involve taking a photograph from an old-school album and scanning it to create a digital file, or converting your home movies from clunky VHS to MP4 video files.

The process of digitizing has changed the game in business environments, especially with the strategies required for companies to stay competitive in the current economic climate.

According to the McKinsey Global Survey of executives, participant companies have accelerated the digitization of their customer and supply-chain interactions, and even their internal operations by three to four years. This includes areas such as back-office, production, and R&D processes. 

Here are two examples of digitization of business processes in action:

More and more fast-food and fast-casual restaurants are making the leap from analog person-to-person ordering to giving customers the digital tools to customize their orders and eliminate miscommunication opportunities. In-restaurant kiosks let customers easily place their specific orders, log in to access their favorite items for faster ordering, or input their rewards numbers to pay with points. 

What is Digitalization?

Now it’s time to understand digitization vs digitalization. One of the main differences between digitization and digitalization is that while digitization is about the transfer of data, digitalization is about optimizing the processes for data. Per the Gartner glossary, digitalization is “the use of digital technologies to change a business model and provide new revenue and value-producing opportunities; it is the process of moving to a digital business.”

As the prevalence of digital transformation grows, examples of digitalization become more and more widespread.

Digitalization has sped up the development of new digital technologies such as cloud computing, artificial intelligence, and machine learning. Perhaps we are seeing the incorporation of digitalization the most in light of the shift to remote and hybrid work. According to a McKinsey survey of business executives, 85% of respondents said their businesses have somewhat or greatly accelerated the implementation of technologies that digitally enable employee interaction and collaboration, such as video conferencing and file sharing.

Offices now leverage programs such as Zoom for virtual meetings, Slack for chatting, and Asana for productivity. At Kenway, we use Microsoft Teams to manage operations like storing files in the cloud or hosting client meetings. Microsoft Teams usage has seen rapid growth in recent years, steadily progressing from 150 million active monthly users in 2020 to 320 million active monthly users in 2023. 

Digitalization did not go away with the pandemic. A Gartner poll showed that 48% of employees will likely work remotely at least part of the time after COVID-19 versus 30% before the pandemic. This means that many companies will continue relying on digitalization to make their processes more efficient, simplify business decision-making, and improve business outcomes.

What Is Digital Transformation? 

Digital transformation is the process of leveraging technology, organizational processes, and people to develop or enhance existing business models and revenue streams. Digitization and digitalization are essentially digital transformation’s supporting players. 

In fact, several different platforms are implemented across enterprises to perfect and accelerate the adoption of a more digital-forward workforce. Salesforce is the ultimate example of a tool companies leverage to help them enable enterprise-level digital transformations. Salesforce comprises a suite of cloud-based applications that unify customer data into a single, shared view, turning information into insight. 

As a Salesforce Partner, Kenway partnered with a leading financial services company to help them comply with new regulatory requirements by using Salesforce to implement firm-wide process automation.

The era of automation is here to stay, especially after benefits were realized when organizations were forced to shift to a digital environment in 2020. 

Below are some stats that could help put this migration into a digital-forward world into perspective:

Digitization vs Digitalization vs Digital Transformation 

It’s crucial to understand the nuances between digitization, digitalization, and digital transformation. 

Here are simple definitions of these terms for quick reference: 

In summary, digitization and digitalization lay the groundwork for technological integration and operational efficiency, while digital transformation drives fundamental change, reshaping businesses for sustained relevance and competitiveness in the digital era.

How Digitalization Translates into the Real World 

Kenway recently worked with an industry-leading healthcare solutions provider to define and implement data transformation to support an improved future state. The client faced a worst-case scenario when it learned that the strategic partner it had leveraged to help collect and aggregate data was not only terminating its agreement but also becoming a direct competitor in just 12 months. 

The client’s most significant obstacle was getting all the data from the existing solution provider and migrating that data to the new solution provider. Further complicating the situation, the existing data set had quality issues that needed to be addressed prior to the migration. Kenway delivered this digitally transformative solution:

How to Benefit From Digital Transformation

A thorough understanding of these three terms is essential for their potential benefit to your company. Whether you need help with digitization, digitalization, digital transformation, or some intersection of all three, Kenway is here to ensure your organization navigates the digital landscape with expertise and optimal execution. 

We address your digital transformation requirements by identifying the capabilities and services required to solve your business challenges–it’s never a one-size-fits-all approach. 

Are you ready to accelerate your business processes? Connect with us to learn how we can help with your digital transformation needs.

FAQs

Why is digital transformation important for businesses?

Digital transformation is crucial for businesses to adapt and remain competitive in the ever-changing digital landscape of modern business. Whether pursuing simple digitization or complex digitalization, using the digital tools at your fingertips will push your organization to greater heights. 

How does digitalization affect customer experiences?

Digitalization can aid in customer experiences by simplifying processes for employees, therefore creating more space for employees to develop relationships and serve customers with their full attention. 

What industries are most impacted by digital transformation?

In the world of modern business, digital transformation impacts every sector. A few to pay particular attention to are healthcare, banking, and IT.

Improving Call Center Operations with Speech Analytics

Speech analytics in call centers is a powerful tool used across industries. This practice uses speech analytics to analyze customer-agent conversations for an improved understanding of customer pain points and potential call center improvements. While speech analytics has been used since the early 2000s, recent AI capabilities have introduced more efficient and accurate data analytics based on live call speech analytics. 

Because we know that customers largely prefer call-to-chat, this level of detailed analysis is necessary for call center optimization due to the complexity of spoken human language. The speech patterns, region-specific words and phrases, and emotional cadence of a conversation greatly impact the success or failure of a customer service interaction. The more quickly a conversation can be analyzed for quality assurance, proper call routing, and ensuring regulatory compliance, the better equipped your call center will be to continue serving customers with efficiency.

Understanding Speech Analytics Benefits

Understanding and optimizing contact center analytics is a huge consideration for every organization with a contact center. Contact center analytics considerations range from optimizing your infrastructure, using Business Intelligence tools, and keeping track of essential contact center metrics for accurate reporting. However, all of these analytics components will be obsolete if your contact center speech analytics capabilities are insufficient. If you want to accurately gather contact center data, a robust speech analytics foundation is the way to achieve it. 

Additional speech analytics benefits include:

Key Speech Analytics Metrics and Features

Speech analytics needs are different for every organization based on company size, current business goals, and specific customer needs. There is plenty of room for customization after establishing a speech analytics foundation, but this list details some of the most important KPIs for businesses to track with their speech analytics capabilities:

Common KPIs to Track Using Speech Analytics

These KPIs are clearly useful, but how does speech analytics actually track these performance measures?

Important Speech Analytics Features

Implementing Speech Analytics in Call Centers 

Speech analytics in call centers is clearly crucial, but beginning the process of implementation can feel daunting. The good news is that the implementation process only requires a look at the existing elements of your business—and on the other side, your contact center speech analytics will be headed toward more efficiency and optimization. 

Step-by-Step Guide to Integration

Once speech analytics is fully integrated into your contact center, make a plan for regular system evaluation and optimization. This is not a set-it-and-forget-it system, but rather one that requires attention and monitoring to ensure every piece of data is being tracked efficiently and accurately. Plan to regularly evaluate performance data to ensure alignment with overall business goals and make any necessary adjustments. For example, you may find that while your speech analytics platform is serving your organization well, there is space to explore further AI integration and capabilities.

Contact Center Speech Analytics Challenges 

Speech analytics is a service nearly every industry has adopted for their contact centers. This service provides tangible improvement for customers, agents, and overall business goals for operational efficiency. In its ideal state, speech analytics give contact centers the ability to run smoothly and seamlessly. But roadblocks can occur as a result of speech analytics:

Future Trends in Speech Analytics

Speech analytics is only growing more popular and advanced by the day, and contact centers are eager to see what new capabilities may emerge to increase productivity in the future. 

Current emerging technologies in speech analytics include sentiment analysis advancements, natural language processing (NLP) and integration with AI-driven solutions. Contact centers will continue to benefit from new capabilities that are highly focused on improving customer sentiment understanding, creating a more personalized experience for customers from the start to end of a call. 

In the future, contact center experts are predicting further potential for enhanced customer personalization, predictive analytics to aid agents during calls, and real-time feedback for quick decision-making.

Conclusion

The future of speech analytics for contact centers is bright. With an emphasis on live AI-feedback and increased customer sentiment understanding, the Kenway team sees a clear path for every organization in any sector to optimize their capabilities with contact center speech analytics. 

No matter the platform or method of implementation your organization chooses, remember that prioritizing enhanced customer experience and agent performance will set your company apart and keep you ahead of the pack time and time again. 

The Kenway team is proud to provide tailored contact center strategies for organizations at any stage of contact center optimization, with expert insight from both contact center and Artificial Intelligence experts. Whether you are just beginning to consider speech analytics for your contact center or you simply need to revamp your existing service, reach out today to start a conversation! 

FAQs

What are speech analytics call centers? 

Speech analytics in call centers is the use of AI and call monitoring to analyze conversations between customers and service agents. 

What are the metrics of speech analytics?

Speech analytics metrics include call sentiment, call duration, call resolution rates, and customer effort score (CES).

What is the difference between voice and speech analytics?

While voice analytics technically refers to the cadence and tone of a voice and speech analytics refers to the actual words spoken, the term speech analytics is commonly used to refer to both.

The Strategic Shift: Project Management vs Product Management

In today’s fast-paced business landscape, companies recognize the need to shift from a traditional project-centric mindset to a more modern product-centric mindset. This transition is not for indulgence of a buzzword; but rather represents a fundamental change in how businesses conceive, develop, and deliver value to their customers. But why is this shift necessary, and what product management benefits does it bring to an organization? Let’s explore.

Project Management vs Product Management: Understanding the Difference

A project-centric mindset (“project management”) focuses on the completion of specific tasks within a defined timeline and budget. The objective is to deliver a particular output or deliverable with success measured by an on-time, on-budget delivery. In contrast, a product-centric mindset (“product management”) focuses on the continuous development and improvement of a product throughout its lifecycle. The primary objective is to create and sustain value for both users and the business with success measured by customer satisfaction, product adoption, and adherence to strategic business outcomes.

Why the Shift from Project Management to Product Management?

The shift from project management to product management is a strategic move that can enable a company to see many long-term benefits:

Customer-Centricity: Projects often prioritize meeting deadlines and budgets over delivering real customer value, which can result in products that, while completed on time, do not meet user needs or market demands. Product management, especially when aligned with agile product management, places the customer at the center, continuously iterating and improving based on feedback and usage data. This ensures that the product evolves in alignment with user expectations and market trends.

Agility and Flexibility: Projects typically follow a fixed scope and timeline, making it difficult to adapt to changing market conditions or emerging technologies. In contrast, product management embraces an agile methodology, allowing for ongoing adjustments and refinements. This adaptability is crucial in a rapidly changing market environment.

Long-Term Value Creation: Projects are transient, with an emphasis on completing a set of tasks. Once a project ends, the team’s involvement usually diminishes, potentially leading to a lack of ownership and accountability for long-term success. Product management, however, is continuous, focusing on the product’s entire lifecycle. This approach ensures sustained effort toward improvement, maintenance, and innovation, leading to long-term value creation for both customers and the business.

Cross-Functional Collaboration: Projects often operate in silos, with teams working on their specific tasks without a holistic view of the product’s impact on the customer or business. Product management fosters cross-functional collaboration, bringing together different departments such as development, marketing, sales, and customer support. This integrated approach ensures that all aspects of the product are aligned towards common goals.

Market Responsiveness: Projects can suffer from a lack of responsiveness to market changes because of their fixed nature. Product management, being inherently market-driven, continuously gathers and analyzes market data to guide product decisions. This responsiveness helps companies stay competitive and relevant.

Innovation and Iteration: Projects may conclude with the delivery of the initial version of a product, with limited scope for subsequent innovation. Product management, however, supports continuous iteration and innovation. By constantly seeking customer feedback and experimenting with new ideas, product teams can keep the product fresh and competitive.

What Transitioning Looks Like and How Kenway Can Help

Shifting from project management to product management involves significant changes in mindset, skillsets, and processes. The mindset shift requires teams to focus on product outcomes that create sustained value for the customer, rather than project outputs that prioritize business objectives. Investing in product management skills is crucial for this transition, including providing training, hiring experienced product managers, and fostering a collaborative culture that promotes cross-functional teamwork and open communication. Additionally, implementing agile practices enhances flexibility and responsiveness by continuously gathering and analyzing customer feedback, allowing for real-time adjustments to product strategies to ensure alignment with market needs.

At Kenway, we specialize in helping organizations seamlessly transition from project management to product management by designing an operating model that aligns with the required mindset, skillset, and process changes. Our approach begins with a thorough assessment of your current organizational structure to identify areas where project-focused thinking still prevails. We then design a tailored framework that shifts the focus toward customer-driven outcomes, ensuring teams prioritize long-term product value over short-term project outputs. Through workshops, targeted training, and the introduction of product-centric metrics, we help transform the mindset of your teams and align business goals with customer needs.

To develop the necessary skillsets, Kenway will create a customized talent strategy, focusing on upskilling current employees, cultivating top-tier product management talent, and embedding experienced product leaders within your teams. We also facilitate cross-functional collaboration by dismantling organizational silos, fostering open communication, and establishing governance structures that promote teamwork. Additionally, we integrate agile practices across your teams, introducing iterative planning, sprint reviews, and continuous feedback loops to enable real-time adjustments to product strategies. Through this holistic operating model, Kenway ensures that your organization is fully equipped to adopt product management, adapt to market changes, and drive sustained success.

Conclusion

The shift from project management to product management is a strategic move that can significantly enhance a company's ability to deliver value, innovate, and stay competitive in a dynamic market. By focusing on long-term product success rather than short-term project completion, businesses can better meet customer needs, respond to market changes, and drive sustainable growth. The journey may be challenging, but the rewards are well worth the effort. We at Kenway believe it is a shift worth making and we are more than happy to help you on your way. For any further information you or your company may need, do not hesitate to contact us or email us at  [email protected] for further help and assistance.

Should AI Be Regulated?

As the AI landscape continues to evolve at an unprecedented pace, the question around “should AI be regulated” becomes increasingly urgent. The potential benefits of AI are immense, from revolutionizing healthcare to driving economic growth. However, the risks associated with its misuse are equally significant, ranging from privacy violations to autonomous weapons.

Legislative developments in both the United States and the European Union offer valuable insights into the emerging global AI regulations. California's AI legislation, S.B. 1047, seeks to establish stringent safety standards for AI systems, while the E.U.'s A.I. Act aims to create a comprehensive regulatory framework for the technology.

The California Model

California's S.B. 1047 represents a significant step towards regulating AI within the United States. The bill's key provisions include:

While the bill has garnered support from many, it has also faced opposition from tech industry giants and lawmakers concerned about its potential to stifle innovation. The outcome of this US AI legislation will likely have a profound impact on the development and deployment of AI in the United States and beyond.

The European Union's A.I. Act

The E.U.'s A.I. Act, a landmark piece of legislation, set a global benchmark for regulating AI. The act's key features include:

The A.I. Act represents a significant regulatory effort by the E.U. to balance the benefits of AI with the need to protect individuals and society from its potential harm. However, its effectiveness will depend on its enforcement and the ability of regulators to keep pace with the rapid evolution of AI technology.

Beyond the United States and the European Union

While the United States and the European Union have taken significant strides in AI regulation, it is important to note that the global landscape is diverse and complex. Other countries and regions are also grappling with the challenges and opportunities presented by AI. For example, China has implemented its own AI regulations, focusing on issues such as data security and algorithmic fairness.

The emergence of multiple global AI regulations can create challenges for businesses operating in a global market. Ensuring compliance with varying regulations can be complex and costly. As a result, there is a growing need for international cooperation and harmonization of AI regulations.

Should AI Be Regulated? The Road Ahead

As these legislative developments unfold, it is clear that the regulation of AI is a complex and multifaceted issue. While the United States and the European Union are taking significant steps to address the challenges and opportunities presented by AI, the global regulatory landscape remains fragmented and evolving.

At Kenway Consulting, we believe that a collaborative and forward-thinking approach is essential to ensure that AI is developed and deployed in a responsible and ethical manner. We are committed to working with organizations to develop AI solutions that are safe, transparent, and aligned with the highest ethical standards.

Additional Considerations for AI Regulation

Beyond the specific AI legislation discussed in this article, there are several other important considerations for AI implementation:

Partner with Kenway Consulting

As AI thought leaders, we understand the complexities of navigating the evolving regulatory landscape. Our team of experts can help you:

As AI continues to evolve, it is essential to engage in thoughtful and informed discussions about its regulation. By partnering with Kenway Consulting, you can ensure that your AI initiatives are not only technically sound but also ethically responsible and compliant with relevant global AI regulations. Contact us today to work together to shape a future where AI benefits society while minimizing its risks.

What Is a Cloud-Based Contact Center?

Customer service call centers got their start in the 1960s, and by simply picking up the phone when customers called, provided the most basic version of what we know today as contact centers. 

As communication technologies evolved and customer service became more important to all businesses, call centers eventually evolved into contact centers. While traditional call centers are only for phone calls, contact centers expand those channels of communication across a variety of mediums, including online chats, SMS, and more. 

The second major distinction between traditional call centers and modern contact centers is the data collection and analysis that takes place, leading to many contact centers now being cloud-based. This blog will explore what cloud-based contact centers are, cloud vs premise-based contact centers, along with the benefits and solutions they provide for customer service departments. 

What is a Cloud-Based Contact Center? 

A cloud-based contact center is a contact center solution hosted in the cloud rather than on-premises. This solution leverages cloud computing technology and is easy to scale, flexible, cost-effective, and secure. 

Cloud Versus Premise-Based Contact Centers 

On-premises and cloud-based contact centers have the same end goal — to serve customers more effectively. So why do organizations choose to make the switch from on-premises to cloud-based contact center solutions? And why now?

Scalability:

For organizations running complex contact center operations, scalability is the biggest felt difference between the on-prem and cloud-based contact centers.

Premise-based contact center use requires continuous server purchases over time, regardless of usage trends. Even servers with high storage will eventually hit capacity, and the cycle of buying new servers will continue. 

A cloud-based CCaaS (Contact Center as a Service) model can be automatically scaled for you by your vendor, so adding to your cloud capacity is a no-brainer during high-traffic times and sustained business growth, allowing for organizations to pay-as-they-go.

This works both ways, since a vendor will also scale back your cloud server capacity based on peak call times and seasonal upticks in business.

Staffing: 

On-prem hardwire requires physical storage space and dedicated staff for managing the hardware. As remote work and smaller office spaces increasingly become the norm, many companies cannot justify the space and staff required to store on-prem contact center hardware.

Lifespan:

Hardware lifespan is limited, and upgrading hardware is costly. No hardware replacement is required when using a cloud-based contact center. Instead, your vendor can automatically make upgrades and improvements to your storage solution, so your organization always stays up to date. 

Security: 

Contrary to what some may think, a cloud-based contact center is actually more secure than on-prem. If your organization uses a provider who is taking the most current and compliant security measures, your cloud-based contact center will excel in security, as well as fully mitigating disaster recovery risk. On the other hand, it requires more staff and complex logistics to keep physical hardware safe and secure in your building at all times.

Current Cloud-Based Contact Center Trends 

AI:
It should come as no surprise that AI is making big waves in the CCaaS world. Companies are either implementing IVR (Interactive Voice Response) services for agent support, intelligent flow support, in their contact center strategy, or they are updating beyond IVR to Intelligent Virtual Agents.

CRM Integrations: As competition between CRM and CCaaS providers increases, so does the potential for innovative integration. Partnerships between CCaaS companies and Salesforce, for example, show the potential for native CRM deployment within existing CCaaS solutions.

Personalization:
CCaaS solutions are so advanced that customers now expect personalized interactions from their contact center provider — many may not even realize they’re speaking to a virtual agent to begin with. Customers implicitly know that companies have access to their data and expect it to be used in call center interactions.

Top Industries for Cloud-Based Contact Centers 

Wondering if your industry needs to focus on contact center optimization? Learn from these leading cloud-based contact center industries: 

Telecommunications:

The telecoms industry uses CCaaS on a large scale, given their high volume of customers and high number of use cases for self-service. As these organizations become increasingly competitive, there is an incentive to reduce contact center costs, and cloud solutions are key to accomplishing this objective.  

Banking and healthcare:

The needs of banking and healthcare customers are varied and often urgent. These industries require extensive compliance and security measures, which can take time and tedious repetitive tasks for call center employees. A cloud solution is ideal for these industries as they provide increased capability and IVR options for multiple levels of demand.

Manufacturing and retail distribution: 

Supply-chain-focused organizations require robust contact centers for addressing customer needs, order issues, returns and exchanges, and more. 

Features of Cloud Contact Center Platforms

Cloud-based contact centers come with a variety of capabilities. These will vary based on the provider your organization chooses, but some essential features to be on the lookout for are:

Omnichannel capabilities: As mentioned above, simple call centers don’t cut it for most organizations anymore. Find a contact center platform that has omnichannel capabilities for the places your audience is interacting with the most – WhatsApp, Messenger, and social media DMs are just a few omnichannel options to consider, so your company can show up where your customers already are. 

Real-time analytics: Access to real-time analytics from your cloud-based contact center provider will be crucial for BI reporting and quick, relevant decision-making. 

Reporting access: Certain vendors have paywall access to contact center data and reporting, which is a major setback for any company. If you are struggling with access, remember that this is your organization’s data. Paying for a cloud-based contact center service means you should always have access to the reporting your organization needs. 

Benefits of Cloud-Based Contact Centers

Still on the fence about implementing or transitioning cloud-based contact centers? A few of the biggest cloud-based contact center benefits are: 

Scalability and flexibility:

A contact center solution that suits your company well now may not be a great fit five years down the road. Migrating on-premises contact center solutions is a huge headache compared to the ease of migration that comes through simple cloud-to-cloud transitions. 

Cost savings and reduced infrastructure costs:

While the on-prem versus cloud-based cost comparison will be different for every organization, an on-prem contact center solution is almost always more expensive than a cloud-based solution. Because of their longevity, simple implementation, and ease of access for those who need it, cloud solutions remove the upkeep costs required of hardware and software, as well as storage and staffing costs. 

Enhanced disaster recovery and business continuity:

In the event of a disaster, cloud-based contact centers can continue to operate almost uninterrupted as long as your employees have access to the internet, in contrast to an on-prem contact center, which is vulnerable to power outages and physical damage.

Selecting the Right Cloud Contact Center Software

Choosing the right cloud contact center software comes down to your organization’s unique needs. Almost every CCaaS provider will meet your contact center needs on a basic level, but we encourage you to truly evaluate every vendor available to determine who will truly be a good fit. 

Some cloud contact center software provider options include NICE, Five9, Genesys, and Google CCAI.

Kenway’s Approach 

Kenway is proud to provide a strategic call center solution approach for customer service oriented organizations. Our focus on strategy, implementation, reporting, and support includes thorough vendor assessments and full digital transformation consulting and support from start to finish.

FAQs

What is a cloud-based contact center?

Rather than hosting a contact center on-premises, a cloud-based contact center is hosted online in the cloud. 

What are the benefits of cloud-based contact center solutions?

Cloud-based contact centers provide solutions for organizations including cost savings, increased security, disaster recovery, advanced reporting and analytics, and flexibility. 

What are the main differences between cloud-based contact centers and on-premises contact centers?

Cloud-based contact centers offer greater flexibility, scalability, and remote accessibility, with lower upfront costs and easier maintenance through a third-party provider. While on-premises contact centers offer more control over data and infrastructure, they require significant initial investments, dedicated IT resources, and are less adaptable to rapid changes in demand. The choice often depends on your business's size, budget, and operational needs.

A Guide to Call Deflection Strategies

For those working in contact centers, the term 'call deflection strategy' is likely familiar territory. Companies design a call deflection strategy to redirect incoming customer service calls to appropriate channels, aiming for high efficiency and customer satisfaction. Well executed call deflection strategies create a more streamlined contact center operation that empowers both agents and customers.

In our previous blog, Mastering Contact Center Operations: Key Principles For Successful Call Center Management, we highlighted the key principles for managing these contact center operations, including Intelligent Virtual Assistants (IVAs), Computer Telephony Integration (CTI), and advanced reporting. These are critical components when designing your organization’s call deflection strategy and omnichannel engagement, and it goes beyond that. 

Benefits of Call Deflection

Call deflection offers a multitude of advantages, including:

Call Deflection Strategies and Considerations

A successful call deflection strategy requires careful consideration of your unique goals. How can a call deflection strategy benefit your business? Reduced call volume? Improved customer satisfaction metrics? Clearly defining your objectives requires careful evaluation of trade-offs and practical measurements. No self-service option or deflection strategy works for every customer or business. 

Call Deflection Implementation 

Modern-day Contact Center as a Service (CCaaS) solutions go far beyond agents, networks, and telephones. It includes a comprehensive suite of technology and process orchestration to ensure service continuity and effectiveness. A well-established implementation plan not only brings your call deflection strategies to life, but also establishes a competitive edge and customer satisfaction over competitors. Listed below are some common best practices to achieve the competitive edge:

A well-designed call deflection strategy benefits both businesses and customers. By implementing a variety of tactics, businesses can streamline operations, empower agents, and boost customer satisfaction. Instead of deploying everything at once, the key to successful call deflection is to continuously analyze, adapt, and leverage the latest technologies to stay ahead of the curve and relevant to business needs. With that, call deflection will continue to remain a powerful tool for exceptional customer service.

Kenway’s Call Deflection Solutions

At Kenway, we specialize in crafting effective call deflection strategies that enhance customer experiences. By leveraging advanced metrics and Intelligent Virtual Assistants, we help organizations reduce wait times and boost satisfaction. Contact us today to learn how we can optimize your call deflection efforts and drive success for your business.

Starting Strong with a New Scrum Team

Taking on a new scrum team or entering a new organization can be both exciting and challenging. At Kenway Consulting, we emphasize a clear scrum evaluation process within the first two weeks to set a solid foundation for improvement.  Our agile transformation services are designed to assess and elevate key Scrum practices, focusing on critical areas such as story quality, retrospectives, and team dynamics. By emphasizing continuous improvement and addressing the common challenges teams face, we enable organizations to move beyond initial adoption and thrive in their agile practices.

Agile Adoption & Maturity Levels
Most organizations have adopted agile methodologies like Scrum, but often struggle with low maturity and a lack of focus on continuous improvement. One of the key reasons Scrum teams stagnate is that they are often asked to do more than their capacity allows. The demand for work exceeds their ability to deliver, and once teams adopt Scrum, there’s a common misconception that they've "arrived." This leads to a halt in pursuing continuous improvement, leaving teams stuck in their current state instead of evolving.

Key Focus Areas for Evaluation
We begin by assessing the team’s Scrum practices across three key areas: stories, retrospectives, and team collaboration.

  1. Evaluating Stories
    High-quality user stories are foundational to any successful Scrum team. We assess:
    • Are developers consistently seeking clarification after sprints start? If so, the stories may be lacking necessary detail.
    • Are reference documents and discussions properly linked and documented within each story? This ensures all stakeholders are aligned and developers have the full picture.

Tactical Recommendation: Implement a Definition of Ready” checklist. Before a story is brought into a sprint, ensure it includes all necessary acceptance criteria, reference materials, and dependencies. This practice guarantees that developers can work without confusion, and it minimizes the need for mid-sprint clarifications.

  1. Optimizing Retrospectives
    Retrospectives are another crucial element for any scrum team. We look at:
    • Is the team consistently holding retrospectives?
    • Is the conversation collaborative or dominated by a Scrum Master or lead developer?
    • Are successes celebrated alongside areas for improvement? Do all team members participate?

Tactical Recommendation: Introduce a rotating facilitator role in retrospectives. Each team member takes turns leading the retrospective, which fosters inclusivity, reduces dominance by a single voice, and encourages broader participation and ownership in the process.

  1. Observing Team Dynamics
    Beyond processes, we assess the scrum team’s overall vibe and collaboration. This “soft skill” evaluation takes time but is essential:
    • Does everyone have a voice, including developers, product owners, and business partners?
    • Does the team feel ownership over its work and decision-making power in how it operates?

Tactical Recommendation: The Scrum Master should take an active facilitation role by ensuring balanced participation in discussions, using techniques like “round-robin” or “silent brainstorming” to give quieter team members space to contribute. They should also model open communication and guide the team toward collaborative problem-solving, helping foster a culture of shared decision-making and accountability.

Where We Start
We prioritize improving stories, retrospectives, and teamwork. A scrum team that excels in these areas is positioned for success, driving higher-quality output and continuous improvement.

By focusing on these elements from the start, we help teams establish strong foundations, fostering a culture that not only delivers value but also thrives over time.  Contact us today tofor learn more about our agile transformation services.

A Guide to Chatbots and Conversational AI Solutions

The way we interact with technology is evolving.  Gone are the days of clunky menus and cryptic commands. Today, users expect a more natural and interactive experience, and that's where chatbots and conversational AI come in.

This blog will equip you with the knowledge to build your own chatbot solution. We'll explore the benefitsadvantages of chatbots, delve into the world of conversational AI, and walk you through the steps of creating and deploying your very own chatbot.

Why Build a Chatbot?

Traditional methods of customer service or information retrieval can be slow and frustrating. Chatbots offer a compelling alternative:

Real-World Use Case: Benefits of Chatbots inTransforming Customer Service

Take Klarna, a financial services company, for instance. This year, they leveraged a conversational AI assistant to handle a wide range of customer service tasks, including managing refunds, returns, and even providing financial advice.  This AI assistant operates 24/7 in 23 markets and communicates in over 35 languages, and in just its first month, it handled two-thirds of Klarna’s customer service chats. This innovative approach has the potential to revolutionize the customer service landscape across various industries.

What is Conversational AI?

Conversational AI, the technology powering chatbots, allows computers to simulate human conversation.  It utilizes natural language processing (NLP) to understand the nuances of human language and generate appropriate responses.  Conversational AI technology is constantly progressing, making interactions with chatbots more natural and engaging.

Pre-Building Your Chatbot

Before diving into the technical aspects, here are some crucial non-technical considerations:

Building Your Chatbot

With a clear vision for your chatbot, let's delve into the technical aspects of its creation. 

Platforms and Frameworks

Here, we'll explore two main approaches: platforms for non-developers and frameworks for developers. Each offers distinct advantages depending on your technical expertise and project needs.

Platforms provide user-friendly interfaces and pre-built components, allowing you to construct a functional chatbot without extensive coding knowledge. They lower the barrier to entry, enabling non-developers to develop.  Two popular options include:

Frameworks offer more granular control over the chatbot's functionality but require coding expertise. The framework providers typically offer a software development kit (SDK) to assist developers in creating applications. Here are two popular frameworks, which can also be used together:

The choice between a platform and a framework depends on your technical skills and project complexity. Platforms are ideal for quick and easy solutions without extensive coding, catering to simpler chatbot functionalities. Frameworks are better suited for developers seeking greater control and customization for complex chatbots with advanced capabilities.

Models and Information Retrieval

Large Language Models (LLMs) are the powerhouses behind your chatbot. These AI models understand and respond to user queries. Here's how to choose the right model for your needs:

Another approach to unlocking external knowledge is Retrieval-Augmented Generation (RAG). A RAG framework empowers your chatbot to access and process information beyond its initial training data. Here's how it works:

By leveraging vectors, RAG can rapidly find relevant information in the external data that aligns with the user's query. This retrieved information is then used to create a more informative prompt for the chatbot's response generation, leading to richer and more comprehensive answers.

Deployment and Beyond

Once your chatbot is built, it's time to deploy it on your chosen platform and test its functionality. Tools like Botium can be used to simulate user interactions and identify potential issues.

After deploying, consider the following:

By continuously monitoring, refining, and improving your chatbot, you can ensure it delivers a valuable and engaging experience for your users.

Here are some additional points to consider as you embark on your chatbot development journey:

Building a chatbot can be a rewarding endeavor.  With careful planning, the right tools, and a focus on user experience, you can create a powerful tool that streamlines interactions, enhances customer satisfaction, and positions your business at the forefront of technological innovation.

The Future of Chatbots

Conversational AI technology is rapidly improving, with exciting advancements on the horizon.  Here are some trends to watch:

By embracing these trends and constantly iterating, you can ensure your chatbot remains at the cutting edge of technology, delivering exceptional value to your users.

Chatbots powered by conversational AI offer a revolutionary approach to user interaction.  Whether you're aiming to enhance customer service, streamline information retrieval, or simply provide a more engaging user experience, chatbots present a compelling opportunity.  With the right planning, tools, and dedication, you can build a powerful chatbot that transforms the way your users interact with your brand.

Ready to build efficient and exceptional user experiences?  Contact us today, and let's discuss how conversational AI can transform your business.

Unveiling the Power of Intelligent Virtual Agents in Contact Center Solutions

In the rapidly evolving landscape of contact centers, businesses need to meet the expectation of seamless, personalized, and efficient customer service interactions. Intelligent Virtual Agents (IVAs) have emerged as a powerful solution for meeting these demands. IVA systems are AI-driven solutions that enable businesses to automate responses and provide human-like, intelligent interactions that align with customer expectations.  

IVA vs. IVR: The Journey from Traditional to Intelligent 

Contact center organizations are transitioning from rule-based, static Interactive Voice Response (IVR) systems to the dynamic capabilities offered by Intelligent Virtual Agents. 

Traditional IVRs operate within predefined rules, provide limited assistance, and struggle to grasp the nuances of natural language. These platforms are a great start for contact centers seeking to serve customers through automation, but they do not allow the flexibility that adjusting to free-speech conversations requires.  

IVA systems represent a leap forward, incorporating AI technologies such as Natural Language Understanding (NLU) and Natural Language Processing (NLP) to comprehend and respond to customers with contextual intelligence. These technologies empower IVAs to understand the intricacies of human language, allowing for more nuanced and context-aware interactions. 

Additionally, IVAs emphasize omnichannel support for an optimized omnichannel strategy that ensures a consistent user experience regardless of whether customers engage through text-based chat, voice interactions, or SMS. 

IVAs also represent the move from traditional data connectivity to a modern data view, as they can analyze vast amounts of customer interaction data and learn from past engagements to enhance future interactions. 

All of these IVA features illustrate just how personalized and innovative IVA systems are when comparing IVAs vs IVRs. 

The Crucial Role of IVAs in CCaaS Platforms 

Like nearly every other industry, contact centers have evolved rapidly towards cloud-based platforms in recent years. Contact Center as a Service (CCaaS) platforms increase flexibility, scalability, and operational efficiency. 

However, the main driver for organizations to move towards CCaaS solutions is that it eliminates the need to maintain on-premises infrastructure, which reduces cost and increases flexibility for remote workers.  

IVAs are a core component of the CCaaS ecosystem. There are many vendors in the market today that offer this service across all channels. The  2023 Gartner CCaaS Magic Quadrant highlights the following vendors as standout leaders: 

Whether voice, chat, text, or a combination of the above, CCaaS providers offer solutions to fulfill client’s needs for more responsive, data-driven, and efficient IVA systems.

IVA Implementation in Contact Centers

The IVA vs IVR conversation marks a significant evolution for contact centers. For companies seeking to stay ahead of the pack in contact center innovation, here are some tips when implementing IVA systems: 

Develop Use Cases

Using IVA systems like a catch-all for your contact center’s potential inefficiencies will not serve your organization or your customers well in the long run. Before implementing your IVA, utilize data analytics to determine where your contact center may be falling behind, and whether an IVA could be the best solution for filling that gap. 

Evaluate IVA Options

Once use cases are identified, it’s time to identify the right IVA provider for your organization. Factors to consider include cost, capabilities, and user-friendliness. 

Test and Monitor Regularly 

Testing your IVA system upon implementation is a crucial element of setting your contact center up for success as it grows and modernizes. Testing early and often will aid in identifying inefficiencies and pain points within the system. Continuous monitoring after the initial testing period is also important to ensure the standards for your IVA system always remain high. 

Contact Center Solutions with Kenway Consulting 

Organizations are embracing IVAs with advanced NLU and NLP capabilities, omnichannel support, and a data-driven approach. The flexibility and cost-efficiency of IVA systems position them as indispensable assets in modern contact center frameworks, offering a pathway to deliver exceptional and consistent customer experiences across diverse channels at a reasonable cost.  

If you’re looking to take the next step in your contact center journey, have questions about IVAs vs IVRs, or aren’t sure how to get started, connect with our Contact Center Solutions experts to begin strategizing for a more streamlined and efficient contact center. 

FAQs:

What are the differences when comparing IVA vs IVR?

IVAs use virtual agents to provide personalized conversations and solutions for contact center callers. IVRs are useful but less advanced tools, which use a prerecorded menu with limited navigation options.

How do businesses use IVR and IVA?

Businesses use IVR and IVA services for contact center optimization. IVRs are often used for automated menu offerings while IVAs can carry on full conversations with customers. 

How to choose between IVA vs IVR?

Many businesses already have IVR capability in their contact center system and may decide that now is a good time to upgrade to an IVA system. This decision depends on the level of optimization and customer service your company desires to provide, but Kenway recommends utilizing IVR systems in order to stay competitive within your industry.

The Comprehensive Guide to Multi-Cloud Architecture

The presence of multi-cloud architecture is representative of the complexity of our digital age. The multi-cloud approach to data management is already the industry standard although it is relatively new, and while it can greatly increase productivity and help companies progress in their data storage capabilities, it also presents challenges in terms of security, cost, and streamlined management.

This article will provide an overview of multi-cloud architecture, from its advent and evolution to current use cases and projected future growth. 

If your organization wants to stay ahead of the curve in multi-cloud computing, keep reading. 

Evolution of Cloud Computing

Like most things in the world of technology, cloud computing has had strong roots in the world of IT for decades, but only in the last 10 years has multi-cloud computing taken the front and center stage as the best practice for organizational data management.

From single-cloud to hybrid to multi-cloud strategies 

When cloud computing came onto the scene, the focus was solely on using an individual cloud to store data. The single-cloud model gave companies and individuals the ability to store data online rather than burdening their physical servers.

As data centers and organizational needs increased, a hybrid-cloud model was developed. This method of cloud computing combined physical data storage with cloud computing for a more diversified, secure, and flexible cloud storage option.

We are now in the age of multi-cloud computing, which has only been commonly used for a handful of years but is now the standard for any enterprise with data storage needs.

Flexibility and innovation in cloud infrastructure

Cloud computing has cycled through three versions of itself in just a couple of decades. While this fast-tracked growth can be overwhelming for business owners and IT departments working to keep up, it is the best and perhaps only way for cloud infrastructure to progress. The modern world of technology moves at lightning speed, and if cloud computing is going to do what it promises — provide security, flexibility, and agility for data storage — it needs to move as quickly as the rest of the IT world. 

What is Multi-Cloud Architecture?

Multi-cloud architecture is the use of two or more cloud services to store, manage, and deliver data for a variety of purposes. Muli-cloud architecture is closely related to hybrid cloud, which is the use of a private, on-premises cloud in tandem with a public cloud. 

Multi-cloud architecture for diverse organizational needs

Every cloud iteration has proven better than the last, and hybrid multi-cloud architecture continues to demonstrate this by supporting diverse organizational needs. When an organization is working across multiple departments, serving various types of clients, and dealing with large amounts of data, a “just okay” solution to data storage isn’t going to cut it. 

Instead, enterprises need what a multi-cloud system provides: flexibility, security, high performance, and low downtime. An additional perk of multi-cloud computing is the variety of cloud providers on the market. Rather than choosing just one provider, organizations can make a la carte cloud choices based on budget, particular storage needs, and available integrations. 

Multi-cloud architecture truly allows organizations to custom-tailor their storage solutions, which helps them see success everywhere else in their business.

The Strategic Importance of Multi-Cloud Architecture

The customization mentioned above means that even competitors in the same field can set themselves apart from one another in the way they deliver services and handle customer data. Multi-cloud architecture creates a world of possibilities for business owners to craft their governance and management strategies in unique ways, rather than being beholden to predetermined cloud computing requirements. This also means that as your business grows and changes, your cloud strategy can grow with you. 

Benefits of Multi-Cloud Architecture

Enhanced reliability through redundancy:

Redundancy implemented with multi-cloud network architecture provides security and peace of mind for your organization. Redundancy means you can store a data set in one location, on one platform, and have it duplicated and backed up on a completely different provider’s service. If an outage or cyberattack impacts your primary cloud, your backups will be secure. 

Optimized performance:

Different cloud providers have different specialties. Some are valued for their cost-effectiveness or security, while others are useful for automation, customer service, or performance monitoring. Capitalize on the potential of these providers by crafting a multi-cloud plan that will play to the strengths of each provider you choose, so you can get the highest benefit every time. 

Improved disaster recovery capabilities and geographic reach:

Similar to reliability through redundancy, multi-cloud architecture removes the risk of losing valuable data in the event of a natural disaster or outage. Storing data in clouds across geographic locations means that if one location becomes inaccessible, your data will still be secure.

Multi-Cloud Challenges and Considerations:

While multi-cloud architecture is a top recommendation from IT professionals and adds many benefits to enterprise data storage, some challenges accompany multi-cloud network architecture as well:

Complexity in management and integration:

The biggest benefit of multi-cloud computing can also be its biggest downfall. Piecemealing together a multi-cloud strategy based on specific offerings from different providers is a great way to tailor your storage needs to your cloud solution, but it can be a headache for governance and management. Data contracts and thoughtful governance plans should be implemented early in the process of adopting a multi-cloud solution to avoid confusion across your enterprise.

Security concerns with data spread across multiple platforms: 

The security that comes from redundancy across platforms is also a double-edged sword. Coordination and alignment across your organization are necessary to ensure security measures are implemented correctly between every department and cloud provider. 

Vendor lock-in risks:

Make sure you fully understand the requirements and contractual obligations of each cloud provider you use before implementing their cloud for your data. The last thing you want is to try to implement a multi-cloud strategy, only to end up locked in with one provider and forced to abandon the rest of your multi-cloud plan.

Planning and Implementing a Multi-Cloud Strategy

There is no one-size-fits-all approach to planning your multi-cloud strategy. The needs of your organization, your existing data systems, and your IT budget are just a few factors to consider when planning a multi-cloud approach.  

Designing a Multi-Cloud Environment

The elements of a multi-cloud environment will vary, but there are multiple design patterns to choose from and services to use for successful design implementation. 

Assessing business needs and technical requirements:

Don’t make multi-cloud strategy decisions in a vacuum. This stage of the process is a great time to pull in stakeholders from across your enterprise to ensure a well-rounded view of your data storage needs is obtained. Interview these stakeholders, find common pain points and growth goals, and begin making decisions about your multi-cloud environment from there. Some business needs to be on the lookout for are scalability, security, user interface, and customer support. 

Selecting the right mix of cloud providers and services:

Choosing your cloud providers takes a great deal of intention and research – ensure the compatibility of your existing cloud services by weighing your choice cloud providers up against your analytics services, such as Microsoft Fabric or Tableau. 

Integration Techniques

Once your cloud providers are chosen and your multi-cloud strategy is laid out, integration is the next step. Strategy is a great start, but implementing multiple cloud providers at once with your pre-existing systems is a significant task. Cloud integration is when the strength of your multi-cloud system will truly begin to shine. 

Seamless connectivity solutions
There are many options and platforms to choose from when integrating your existing cloud services with your new multi-cloud strategy. If you have on-premises cloud storage, focus on creating a hybrid-cloud bridge between your existing private cloud and new public clouds. The most important aspect of integrating your cloud platforms is a seamless integration experience — focus on a system that will be efficient and secure, with limited down time. 

Another method for seamless cloud integration and development is containerization through tools like Kubernetes. These containerization tools allow your organization to develop cloud-native apps, adjust workloads, and grow in flexibility across cloud providers.
Pro tip: While considering your integration tools and methods, it’s also a good time to evaluate whether your data is being housed in the most efficient way. A data lakehouse is the most flexible, cost-efficient, and secure form of housing and organizing structured and unstructured data. 

Security and Compliance

One consideration of hybrid multi-cloud architecture is ensuring security and compliance measures are stringently followed across every cloud platform. 

Internal, company-wide measures can be taken to educate your team on data security, set up guardrails for data access, and establish expectations for best practices – because although security platforms and data restriction can go far for your company’s privacy and security, individual users are interacting with this data every day, and they ultimately have responsibility for the handling of important data.

One highly effective way to establish governance and compliance across your company is to implement particular contracts, policies, and governance norms that can be agreed upon by every team member.

Operationalizing Multi-Cloud Architecture

Now that your multi-cloud strategy has been established, your integration tools have been chosen, and governance policies have been laid out for your organization, it's time to use your cloud strategy in real time. 

A multi-cloud management tool can significantly reduce your workload in managing multi-cloud architecture, and there are multiple options to choose from.

To discern which multi-cloud management tool is best suited for your organization, weigh your priorities and greatest needs. Are you most concerned with cost savings, Kubernetes management, governance and security, or hybrid to multi-cloud integration? 

Make a priority list and discover which tool may be right for your organization. Multi-cloud management tools to explore include:

Cost Management and Optimization

Multi-cloud architecture integration and management tools are important for the growth and success of your business, but the cost of these premium providers can add up. A few ways to mitigate excessive spending on cloud tools is to ensure there is no idle spending on certain platforms through constant monitoring and reallocation of resources based on current needs. 

Remember that the benefit of multi-cloud architecture is the inherent customization, so take advantage of that and adjust your cloud provider allocations based on your business growth and current needs. 

Some cost-monitoring and management tools include Azure Cost Management, Amazon CloudWatch, and CloudHealth. 

Case Studies and Real-World Applications

Kenway successfully aids enterprises in their hybrid to multi-cloud deployment, from organizations at the national level to small businesses. These companies are seeking assistance in everything from growing in their understanding of their buyer's needs through Salesforce to establishing cloud redundancy and increasing organizational security. 

The possibilities of success that can come from your organization’s investment in multi-cloud architecture cannot be overstated. See for yourself how one of our own clients scaled their operations through technology modernization and a multi-cloud solution.

Future Trends in Multi-Cloud Architecture

Multi-cloud architecture has made large strides toward further data integration and sophisticated data storage and use, but if we know anything about the world of IT, it's that things move more quickly than most anyone can predict or expect. 


AI and machine learning

AI is a game changer for the entire digital world, and the cloud is by no means excluded from its impact. AI and machine learning can fill in the gaps for organizations without team members being proficient in every cloud or management platform, as well as aiding in optimization and analysis. 

Edge computing 

Edge computing is a form of physical storage that places data storage as close to the data source as possible, cutting out the centralized cloud approach for a decentralized approach that can be more efficient and secure in certain scenarios. 

With so many types of data and organizational needs, edge computing and cloud computing should be able to coexist with no issue — in short, there is plenty of demand for both. 

Summarizing Multi-Cloud Benefits

Now that we have walked through the history, benefits, challenges, integration, security, cost roadblocks, and management tools that go along with multi-cloud orchestration, you should have a comprehensive understanding of what platforms and providers will best set your organization up for success as you transition to a multi-cloud system. 

While the initial setup and implementation is a large lift, remember that multi-cloud is the way of the future for digital enterprises. The sooner you begin implementing your multi-cloud architecture, the more of a competitive edge you will have in the fast-paced digital environment. 

For organizations just starting with multi-cloud implementation, Kenway recommends laying out your cloud strategy priorities and gathering insight from stakeholders across the company. Have a plan in place for every provider that will be needed to make your company’s cloud integration a success, from providers to internal governance. 


Lastly, remember that multi-cloud architecture is far from one-size-fits-all. The unique needs of your particular business should dictate the choices made for implementing this new structure – be attentive to what those inside of your organization are saying, and stay cognizant of advice received from multi-cloud experts. 

If expert advice is an area where your enterprise needs support, Kenway would love to supplement those needs with our team of consultants. Kenway is proud to offer tailored multi-cloud strategies based on your enterprise's current needs, growth plans, and security requirements. 

Multi-Cloud Architecture FAQs

What are the benefits and risks of multi-cloud architecture?

Multi-cloud architecture benefits include increased disaster recovery capabilities, security through redundancy, and data flexibility. On the other hand, risks of multi-cloud architecture can arise when governance is not taken seriously by an organization and its team members, and when cost-savings are not taken into account from the start of implementing a multi-cloud strategy. 

How does multi-cloud architecture enhance security and compliance?

Multi-cloud architecture requires a high level of intentional security and compliance because of the various cloud providers being used at once. The elevated security risk can actually be a benefit because of the level of intention and coordination required to ensure a consistent security plan across the board.  

What strategies should organizations adopt for effective multi-cloud integration?

Use a containerization or organizational tool like Kubernetes for effective multi-cloud integration, as well as planning well beforehand and focusing on preparation for reduced downtown during integration efforts.