SL-101820-36860-11-1030x687 Cloud Migration: Common Challenges and Recommendations

Introduction

It is estimated that today more than 90% of companies are already using some form of cloud services, while by 2023, the public cloud market is projected to reach $623.3 billion worldwide. These statistics highlight the consistent emerging pattern of businesses migrating their infrastructure from on-premises to the cloud. Industry pundits also claim that it’s no longer a question for companies to ask if they should move to the cloud but rather when.

There are several reasons to it. Adopting the cloud offers improved data access, scalability, and application security while achieving enhanced operational efficiency. A projection by Oracle also predicted that companies can save up to 50% on infrastructure expenses by deploying workloads to a cloud platform. 

However, transitioning to the cloud comes with its own set of challenges, with a disclaimer that not every cloud migration project goes as smoothly as intended. While there are a number of factors to failure, a lack of planning and insight before cloud migrations are one of the most prominent reasons for an outright failure. This not only means that the organization’s long-term goals to improve operational efficiency goes for a toss but also result in wasted effort, time, and money.

This article addresses the most common challenges to expect when moving from an on-premises setup to a cloud platform, and how to overcome them.

Common Challenges of an On-Prem to Cloud Migration

As an essential best practice, organizations are required to diligently research and assess the most suitable processes, methodologies and plan every step of the migration to ensure the right decisions are made, and costs are controlled. Here are some key considerations that should be followed as the rule of thumb. 

Choosing the Right Model and Service Provider

Choosing the right cloud model for a business and the right service provider can not only make or break the migration project, but also affect its future maintenance and sustainability. 

There are 3 cloud models that require an assessment to ascertain the best fit for the company:

  • Public Clouds are the most popular choice where a service provider owns and manages the entire platform stack of cloud resources – which are then shared to host a number of different clients. Some common examples of such managed service providers are MS Azure, AWS, and Google Cloud.
  • Private Clouds, on the contrary, don’t share computing resources as they are set up specifically for exclusive use by a single organization. Compared to public clouds, such a framework offers more control over customized needs and is generally used by organizations who have distinct or specific requirements, including security, platform flexibility, enhanced service levels, etc.
  • Hybrid Clouds are a blend of a public/private cloud used with an on-premises infrastructure. This allows an organization to interchange data and applications between both environments that suit its business process or technical requirements. For businesses that are already invested in on-site hardware, a Hybrid cloud model can ease a gradual transition to the cloud over a long-term period. Additionally, for businesses that are too reliant on Legacy applications, a Hybrid cloud model is often perceived as the model that provides the leeway to adopt new tools while continuing with traditional ones. 

Challenges-of-Cloud-Migration-e1617044236232 Cloud Migration: Common Challenges and RecommendationsImage source: Intel.com

Apart from the cloud model, when it comes to selecting a service provider, there are key factors to consider such as 

  • how the data is secured, 
  • Agreed service levels and the provision to customize them, 
  • a guarantee of protection against network disruptions, and 
  • the costs involved. 

It is important for an organization to be mindful of vendor lock-in terms, as once the transition starts with migrating data, it can be difficult and costly to switch providers.

What is recommended?

Plan exhaustively on analyzing the current and future architecture, security, and integration requirements. Be clear about the goals of migrating to the cloud and identify the vendors that will most likely help in achieving them. A best practice of choosing the preferred service provider often starts with evaluating the proposed Service Level Agreement (SLA) for maintenance commitments, access to support, and exit clauses that offer flexibility.

Engagement and Adoption from Stakeholders

When introducing changes within an organization, it is often met with resistance by multiple stakeholders, which can thwart efforts for a smooth switch. This can be explained by scenarios where – the finance department may oppose the transition because of cost, the IT team may feel their job security is threatened, or the end-users won’t understand the reason for the change and fear their services might get impacted. Though such resistances are usually short-term, such factors may often compromise an organization’s immediate goals unless stakeholders are onboard.  

What is recommended?

Dealing with stakeholder resistance requires a holistic change in mindset across all levels of the organization. While hands-on training and guidance may provide support for users in adopting and using cloud-based services, preemptively addressing any resistance is a start on the right foot. Additionally, as an advisory for various organizational units, it is suggested to build a compelling business case that highlights current challenges in the organization with clear explanations on how migrating to the cloud will resolve these issues. 

Security Compromise

Whether the underlying architecture relies upon on-premises or the cloud, protecting a company’s data remains a top priority for any organization. When migrating to the cloud, a large part of the organization’s data security is managed by the cloud service provider. As a result, it is vital to have a thorough assessment of the vendor’s security protocols and practices.

This also means that organizations remain in control of where the data is stored, how incoming/outgoing data is encrypted, what measures are in place to ensure software is updated with the latest fixes, as well as the regulatory compliance status of the provider. Certain enterprise cloud providers like MS Azure take a holistic approach to security and offer the highest industry security standards that are aligned with regulations like PCI and HIPAA. 

What is recommended?

Define in-house security policies and explore the available cloud platform’s security tools. As a result, it is critical to proactively consider: 

  • authorization & authentication, 
  • audit lifecycle, 
  • application and network firewalls, 
  • protection against DDoS attacks and other malicious cyberattacks. 

Besides, a secure cloud migration strategy should administer how security is applied to data in-transit and at-rest, how user identities are protected, and how policies get enforced post-migration across multiple environments. 

It is important to note that administering security across all layers and phases of implementation requires much more than using tools. This usually begins with:

  • an organization to foster a security mindset
  • adopting security as part of the workflow by embracing a DevSecOps model, 
  • as well as incorporate a robust policy and audit governance through Security-as-Code or Policy-as-Code methodologies. 

Avoid Service Disruptions

Legacy models that rely extensively on third-party tools which are through with sunset clauses, or in-house developed applications, require special provision for a smooth transition. More so, frameworks involving virtual machines that include hardware-level abstraction are practically more complex that syncs and maintains abstraction layers through pre and post-transition phases. Unplanned migrations for such setups may often lead to performance issues including increased latency, interoperability, unplanned outages, and intermittent service disruptions. 

What is recommended?

Replicating virtual machines to the cloud should be planned based on an organization’s workload tolerance, as well as its on-prem networking setup. It is advised to make use of agent-based or agentless tools available by service providers, such as Azure Migrate that provide a specialized platform for seamless migrations. 

As for legacy or sunset apps, organizations are advised to plan for Continuous Modernization that provisions regular auditing of such apps, while planning for a phased retirement in the longer term. For setups where an immediate Lift and Shift isn’t an option, the organization should recalibrate its migration strategy by considering Refactoring or Rearchitecting strategies, that reimplements the application architecture from scratch. 

Cost Implications

Accounting for near and long-term costs during cloud migration is often overlooked. There are several factors that require consideration to avoid expensive and disruptive surprises. As migration from a legacy to the cloud is gradual, in the immediate term, organizational units often need to continue using both on-premises as well as the cloud infrastructure. This implies additional costs towards duplication of resource consumption such as – data sync & integrity, high-availability, backup & recovery, and maintenance of current systems

What is recommended?

Over the longer term, using a cloud platform is more cost-effective. Though there is very little that can be done by an organization to avoid most of such expenses during migration, what is required is to include these within its financial projections. While doing so, expect there to be upfront costs related to the amount of data being transferred, the services being used, and added expenses that may arise from refactoring to ensure compatibility between existing solutions and the cloud architecture. 

Benchmarking Workforce Skills

A migration plan that doesn’t benchmark workforce skills is often considered flawed. Cloud migrations can get complicated with customized requirements, using new technologies, and assessing what systems and data will be moved. During this, a good chunk of the effort goes towards the analysis of existing infrastructure to establish what will work on the cloud and identify the future gaps with respect to in-house workforce skills. 

What is recommended?

Migrating to the cloud is a complex process that requires a unique set of soft and hard skills. Before transitioning, it is essential to understand what practical knowledge the team has with cloud platforms, and then take the necessary steps to upskill in relevant cloud technologies and security. An important consideration around this should also factor in the allocation of contingent funds towards setting up a consistent framework of skills upgrade for seamless adoption of emerging tools and practices.

Key Takeaways

Adopting a cloud framework today is more a necessity than a projected goal. While migrating to the cloud, an organization’s goal remains equally important to develop a migration strategy, that sets realistic expectations by undertaking thorough due diligence. Being aware of the challenges and how to address them, not only minimizes immediate risks, but also prevents the project from becoming a disaster in the longer run.

By the end of it all, the successful strategy determines how efficient the migration is, without a noticeable impact on productivity or operational efficiency.

Microsoft-Ignite-Announcements-2021 Microsoft Ignite Announcements 2021

 

Microsoft Ignite hosted their second virtual conference in 2021, and had so many exciting speakers and announcements, that we thought we should dedicate an article to some Microsoft Ignite announcements. Microsoft Ignite was started in 1993 and is an annual conference of developers and IT professionals. They gather to discuss new developments in cybersecurity, AI, and Azure innovation, as well as listen to brilliant keynote speakers. Microsoft Ignite 2021 took place from March 2-4 and we want to tell you some of the most exciting projects that were shared during the event. 

Microsoft Teams Update

Microsoft Teams has undergone a plethora of updates, many of which are new video call features to increase ease of meetings and functionality. “Dynamic mode” is one of those new features. It automatically adjusts to the meeting experience based on the users and content, allowing for easy transitions based on the meeting itself. “Powerpoint Live” is another one to try out! The presenter can see what the others are viewing without switching screens. This allows for virtually seamless presentations without worrying whether the right presentations are being shared or the slide is correct. Along with Powerpoint Live, Microsoft Teams now has “Presenter Mode”, which has created more options for presenters to have polished and interactive presentations. Finally, Microsoft Teams addressed a cybersecurity concern by creating “invite only meeting controls”, making sure that only the relevant people are allowed into a call. 

Microsoft Power Platforms Update

Some of the other exciting Microsoft Ignite announcements have to do with Microsoft Power Platforms. The popular low-code, development platform for experienced coders and business users alike has taken companies by storm. Some of the features that experienced upgrades in 2021 are Power Apps, Power Automate, and Power Virtual Agent. Power Apps, Microsoft’s low-code program that allows everyone to build and share apps, now has offline mobile capabilities, geospatial capabilities like maps, and more. Power Automate, Microsoft’s automation platform that allows for greater productivity and secure automation, has made shared desktop flows available across organizations. And finally, Power Virtual Agent, that allows users to create their own chatbots with ease, now includes data loss prevention options as well as new topic trigger management for the chatbots. For more information on Power Platforms Updates, click here.

Azure Arc Updates

For those who haven’t heard of Azure Arc, it’s a set of technologies that innovates Azure management and services to any platform. They have also undergone extensive updates this year. Firstly, they have made it possible to run machine learning everywhere. Microsoft shares, “By using Azure Arc to extend machine learning (ML) capabilities to hybrid and multicloud environments, customers can train ML models directly where the data lives using their existing infrastructure investments. This reduces data movement while meeting security and compliance requirements.” Next, they expanded on their program by allowing users to build cloud native applications at scale, anywhere. Azure Arc enabled Kubernetes is now generally available. To learn more, read the full article from Microsoft. And finally, in collaboration with Azure Stack HCI and Azure Arc, users are able to modernize their data centres with ease. It’s a cost-efficient hyperconverged infrastructure (HCI) solution, all managed through Azure. To learn more about Azure Stack HCI, click here.

Data and AI Announcements

Another exciting Microsoft Ignite announcement has to do with Azure Percept, Microsoft’s platform that simplifies the usage of Azure AI technologies on the edge. This includes Azure Cloud offerings such as AI model development, analytics, and more. The platform even includes a development kit, which comes with an intelligent camera: Azure Percept Vision. Want to learn more about this exciting product and how Microsoft is increasing accessibility? Read the full article from them here.

Additional Resources

We’ve touched on some of the updates and announcements that happened at the Microsoft Ignite Conference 2021, but we’ll share just a few more highlights in case you would like to check out additional resources. 

Microsoft Virtual Training Days

If you’re interested in gaining more hard skills, taught by an experienced instructor in your language, check out Microsoft Virtual Training Days here

Keynote Presentation by Satya Nadella

At the conference this year, Satya Nadella, CEO of Microsoft, gave a keynote speech on Microsoft’s vision for the future of Mixed Reality. You can watch the full presentation here to learn more. 

Learn about Cybersecurity

And finally, learn more about cybersecurity, compliance, identity and management in this video from the conference. 

 

We hope that you learned something from these Microsoft Ignite announcements, and feel free to reach out to us at info@optimusifo.com with any further questions.

 

pexels-christina-morillo-1181341-1030x688 Essentials of Data Governance

In the era of emerging technologies, data has become essential for organizations. With rapid digital transformation across industries, gaining a competitive advantage is crucial for thriving in the market. Today, data is the new “oil” that forms an organization’s core for business growth. However, the rate of data generation has become enormous. A recent report by Towards Data Science produced the statistics of data generation that stands at a whopping  2.5 quintillion bytes. Additionally, the current projections state the data generation rate to rise to 133 zettabytes by 2025.

In recent years, the increase in the number of data breach cases has doubled. The imminent threat in a business is the possibility of data breaches. To bolster data protection, it is of utmost importance to have a robust data governance framework. As per IBM data breach reports, the average cost of a data breach is highlighted as $3.86 million, while the USA alone recorded a breach of $8.64 million.

There is a need for robust data governance framework to tackle such challenges. Standard data governance ensures data security, data quality, and integrity while providing the traceability of the data origins. Also, data governance can be successfully implemented when high-quality data is readily available with crucial information on the data types, which is achievable with a data catalog.  Besides, an organization attains firm control over its data usage policies when a regulatory body imposes stricter guidelines. Today, it is possible with some of the robust regulatory bodies available that put a strong emphasis on data governance. Among them, the most well-known is the General Data Protection Regulation (GDPR). Furthermore, a data governance approach can reach its ultimate goal within an enterprise with its essential components, namely processes, policies, access controls, and data protection, encompassing the entire data-related workflow within an organization. Tech giants such as Microsoft have contributed significantly to the data governance requirements with the Azure Purview offering that has reach achieved wide acceptance in the industry.

The article delves into the topic to provide a deep insight into data governance and its regulations.

Data Governance Overview

Data governance is a strategy that incorporates the practices, processes, and technical requirements of an organization into a framework by which an organization can achieve standardization in its workflow, thereby providing protection and the appropriate management of its data assets. A useful data governance model’s scalability is a must as it ensures that all the policies, processes, and use-cases are applied accurately for transforming a business into a data-driven enterprise.

Another crucial aspect of data governance is for an organization to conduct a risk assessment and compliance. The successful integration of data governance is determined by efficient data management and data security factors within the framework. An ideal governance policy must address the critical components of data storage,  the original source, and a well-defined data access strategy. Furthermore, data governance solutions focus on providing response plans relating to misuse of data and unauthorized access.

Data governance and data management are often used synonymously, but it is essential to understand that data governance forms a significant part of a data management model.

Data Catalog

A data catalog acts as the inventory of the critical data assets in an organization. The use of metadata helps to manage the data more efficiently. The data professionals benefit from a data catalog as it helps in data collection, organizing data, easier accessibility to data, and improvement of the metadata to support data discovery and governance. While the data generated is enormous in a day to day functioning of an organization, finding relevant data becomes challenging for specific tasks. Additionally, data accessibility is demanding due to various legal regulations of the organization and a particular country’s government. The key factors to understand are the data movement within an organization, such as the individuals who will have access to it and the purpose they want to access it. Such tracking of the data ensures the protection of the data as it limits unauthorized personnel. Thus a data catalog plays a crucial role in addressing some of the challenges related to data.

  • A data catalog provides all the essential data required by an organization; therefore, data accessibility from a single point ensures reduced time for searching data.
  • Creating a business vocabulary.
  • Efficient transformation of data lakes into data swamps.
  • Identifying the different structures of the data.
  • Availability of high-quality and reliable data.
  • Data reusability possibilities

An organization can achieve a competitive advantage with the appropriate use of data. Therefore the data should be trustworthy from the appropriate sources. Some of the organizations’ key members, such as C-level executives, use data for business decisions. Thus, a data catalog becomes useful for looking at cost-saving and operational efficiency factors with a keen eye on fraud and risk analysis.

Data Governance Framework

A data governance framework allows an organization to focus on achieving the business goals and data management challenges while providing the right means to attain them more speedily and securely. Besides, the results of a data governance integration are scalable and measurable.Key-Participants-in-a-Data-Governance-Framework Essentials of Data Governance

Figure. Key Participants in a Data Governance Framework. Source

 

Some of the essentials of a data governance framework are:

  • Use Cases

The data governance framework must address some critical factors, such as the use case for several business scenarios in an organization. The data governance use cases should interlink the need for a data governance framework and its contribution to achieving business goals. Ideally, the use cases are derived from significant factors in an organization, such as revenue, cost, and the associated risks. The category-related use case addresses the enrichment of products and services, innovations, market opportunities, and the ability to achieve them at a reduced cost of maintenance with efficiency, auditing, and data protection.

  • Quantification

The need to quantify data is an absolute necessity as it produces data governance integration in the organization. A business needs to ascertain that they are following, covering all the categorized use cases with evidence to monitor the performance and provide future insights.

  • Technical Benefits

With the technical addition in a workflow, the data governance solutions can efficiently address some of the critical components, thereby ensuring efficiency. The data governance must address factors like the need for technology investment and the primary members who will work with data-related processes. A technical infusion in the workflow also enables the easier discoverability of data definitions, data categories, data lineage, and the appropriate classification of data as trustable data or untrustworthy data. The technical addition also makes it possible to create a feedback mechanism for resolving regulatory issues and policies concerning data usage.

  • Scalability

The data governance policies should be capable of providing scalable results. Using a scalable model provides growth opportunities for an organization by addressing the problems in a data lifecycle. The primary focus is to introduce new tools to reduce operational costs and provide data protection for business growth.

Data Governance Processes

The data government processes comprise of the following.

  • The organization must be mindful of the essential documents such as regulatory guidelines, statutes, company policies, and strategies.
  • A clearly defined workflow states legal mandates, policies, and objectives to be synchronized to help an organization meet data governance and management compliance.
  • Data metrics to be incorporated to measure the performance and the quality of the data.
  • Principles of data governance to be met.
  • Identification of the data security and privacy threats.
  • Control measures to ensure smoother data flow with a precise analysis of the risks.

Data Governance Policies

Under data governance, there are various policies to determine the effectiveness of the organization’s operational strategies. Some of the policies related to data accessibility, data usage, and data integrity are incredibly crucial for successful data governance implementation. The most important policies that an organization must follow for successful data management are as follows.

  • Data Structure policy
  • Data Access Policy
  • Data Usage Policy
  • Data Integration Policy

 Privacy and Compliance Requisites

The organizations are associated with a significant amount of highly sensitive data. Therefore, an organization needs to follow the regulatory compliance of data governance. In the context of business, privacy refers to an individuals’ right to have control over the type of personal data they want to be collected and used and the sensitive information that should be restricted. As per EU directives for data governance, sensitive data is defined as the data that contains a name, address, telephone number, and email address of an individual. On the other hand, sensitive personal data is distinguished clearly, as the data contains information on a person’s ethnicity, political opinion, religion, race, health-based information, criminal conviction, and trade union-based membership details. Such data have stricter guidelines that must be followed with due diligence.

Role of General Data Protection Regulation (GDPR)

The General Data Protection Regulation (GDPR)  was established in the year 2016. The primary aim of the regulation was to provide a framework for data privacy standards. GDPR states that any company looking to conduct business in Europe must be willing to adhere to data protection norms. The GDPR has strict guidelines that ensure the protection and privacy of personal data for its citizens. The mandate was an update from the previous Data Protection Directive in Europe.

Crucial-Requirements-of-GDPR- Essentials of Data Governance

Figure. Crucial Requirements of GDPR. Source

 

Under GDPR, the mandate’s scope extends its reach in terms of the territorial horizon while providing a well-defined law for processing personal data by offering their business services in Europe. The organizations or individuals aiming to provide their services without the presence in Europe are monitored for their service offering under GDPR guidelines. The tracking of such services includes online businesses that require users to accept cookies to access their services. GDPR also differentiates the various data types and the data considered personal data under the mandate.

Furthermore, the direct and indirect data are interlinked with the identification of data subjects. The data subjects are people who can be identified with their information presented in the data. The data in this context is related to personal information such as names, addresses, IP addresses, biometric data logs, citizenship-based identification, email, and the profession.

Additionally, the GPPR mandate ensures that the data is collected within the limits of the law, and it should be highly secured while it exists the records of the organization with stricter rules for its uses. The primary categories of GDPR data governance requirements are:

  • There must be a classification of personal data, while personal identification data must have limited usability. The individuals can access their data and hold the right to request personal data removal or rectification. The mandate also states mandatory data processing requirements and portability of data.
  • Data protection is a must, and it should cover all aspects of safeguarding personal data collected. Also, there must be confidentiality, integrity, and availability of the data collected for business purposes. The organizations should also adhere to data restoration regulations for scenarios that may involve data loss due to technical failure or accidents.
  • The collected data must be well- documented as per legal procedures.

Access Controls

Access controls form an integral part of access governance that regulates the accessibility of data. The critical areas covered comprise the guidelines to specify who can access the data and view it. Additionally, it specifies that there is a requirement to state the purpose of data access in the organization. The compliance of access controls allows eliminating unauthorized access of data.

As per the GDPR mandate, some of the data protection requirements must enforce specific procedures.

  • There must be accountability associated with data protection requirements. Data protection personnel must be appointed to manage data and monitor its activities for organizations involved in data processing activities. The appointed individuals must ensure that the data protection standards are met.
  • Data storage is the essential factor for data privacy. Therefore, organizations must have a data map and data inventory to track the source of data and its storage. The source includes the system from which it was generated while tracking the data lineage to provide comprehensive data protection.
  • Data accuracy is paramount, and organizations must keep up-to-date data to achieve high-quality data. Also, data quality reporting must be followed to keep up with data quality standards.

Data Protection

  • Data intelligence provisions for getting insights with 360 visibility of data.
  • Identifying data remedies for security and privacy issues.
  • To protect sensitive data with access governance and ensure no overexposed data exists with data governance methods.
  • Integrating artificial intelligence capabilities to identify dark data and its relationship.
  • Assigning labels with automation to provide data protection during the workflow and the lifecycle of the data.
  • Rapid data breach notification and its investigation.
  • Automate procedure for classifying sensitive and personal data.
  • Automated compliance and policy checks.
  • In-depth assessment of risk scores with metrics depending on the data type, location, and access consent.

Reimagining Data Governance with Microsoft Azure Purview

Azure Purview is a unified data governance service by Microsoft. The governance service enables management and governing of on-premise, multi-cloud, and software-as-a-service (SaaS) data. The users can have access to a holistic and up-to-date map of the data with automated data discovery. Besides, the classification of sensitive data is more manageable along with end-to-end data lineage. With Azure Purview, the data consumers are assured of valuable and trustworthy data.  Some of the key features of Azure Purview are discussed in the following section.

  • Unified mapping of data

The Purview data map feature establishes the foundation of practical data usage while following the data governance standards. With Purview, it is possible to automate the management of metadata from hybrid sources. The consumer can take advantage of data classification with built-in classifiers that can Microsoft Protection sensitivity labels. Finally, all the data can be easily integrated using Apache Atlas API.

unified-data-mapping Essentials of Data Governance

Figure. Unified Data Mapping using Azure Purview. Source

 

  • Trusted Data

Purview offers a data catalog feature that can allow the easier search of data using technical terms from the data vocabulary. The data can be easily identified as per the sensitivity level of the data.

  • Business Insights

The data supply chain can be interpreted conveniently from raw data to gain business insights. Purview offers the option to scan the power BI environment and the analytical workspace automatically. Besides, all the assets can be discovered with their lineage to the Purview data map.

  • Maximizing Business Value

The SQL server data is more discoverable with a unified data governance service. It is possible to connect the SQL server with a Purview data map to achieve automated scanning and data classification.

  • Purview Data Catalog

The Purview data catalog provides importing the existing data dictionaries, providing a business-grade glossary of terms that makes data discoverable more efficiently.

Conclusion

Business enterprises are generating a staggering amount of data daily. The appropriate use of data can be an asset for gaining business value in an organization. Therefore, organizations need to obtain reliable data that can provide meaningful business insights. Advanced technologies such as artificial intelligence and data analytics provide an effective way of integrating data governance in the operational workflow. Today, tech giants like Microsoft, with their data governance offering: Azure Purview, have paved the way for other organizations to opt for data governance. Many startups follow in the footsteps and have acknowledged the importance of data governance for high-quality data while ensuring data privacy at all times, thereby offering several data governance solutions in the market. A robust data governance framework is essential for maintaining the data integrity of the business and its customers.

 

 

tips-for-saas-business-success-scaled-e1615238708300 5 Tips for SaaS Business Success

With February came another exciting event in our webinar series: Learning from the Best SaaS companies, with guest speaker Boris Wertz. Wertz is the Founding Partner of Version One Ventures, a fund that invests in early-stage founders across North America. He has years of experience investing in consumer internet and enterprise companies and was generous enough to share his insights on how to create business success in SaaS. We talked about all things SaaS, from reducing the friction of initial engagement, to one of Wertz’s biggest tips, leveraging the preexisting to build something even more effective. Growing innovation is absolutely crucial and if you keep reading, you’ll learn our top tips for SaaS business success. 

Reducing Friction

When speaking about the critical importance of reducing friction, Wertz shared some wise words. “If you can reduce the friction of engagement for a new user, you’re onto something.” People want a user experience filled with ease, not hard work, and that’s the simple truth of it. The example of YouTube came up in the webinar, and how a lot of their initial success can be attributed to their easy video upload experience for users. It makes the service highly requested and attractive to clients. 

Leveraging the Preexisting

Another tip for the SaaS industry is remembering that there is no need to build everything from scratch. Leverage whatever you can that is already out there! As Wertz puts it, there is a lot of technology and infrastructure that can be “stacked” to create something unique and meaningful. And it has never been easier to do so. In this case, “it makes no sense to reinvent the wheel.”

Capital Efficiency

Capital efficiency was another topic that was touched on during this webinar. Being capitally efficient is one of the most important ways to ensure SaaS business success. Wertz gave the example of Slack, the highly profitable chat room app that connects all members of an organization. When they focussed on capital efficiency, they saw immediate results. Capital efficiency refers to when more annual recurring revenue is created in a year than burned. Something to keep in mind is that a big part of capital efficiency is market efficiency as well. Staying informed about pricing and upselling and expanding your business for current clients can help you stay above the curve and avoid churn. 

Developing a New Category

It’s been said before, but still rings true; if you can find a hole or area of need in the industry and find a way to fulfill it, you’re on the right path. Developing a new category can be difficult but it’s not impossible. The app Slack is an amazing example here as well! They had no enterprise sales at first but as the problem of communication within organizations evolved, they found increased success. One strategy to get started is to solve a small problem for a small group of customers but then expand from there. Wertz gave the example of Hootsuite, the popular social media management platform. They were able to pick up on a trend that needed some work and although they started small, they quickly multiplied in size.

Creating a Great Team

As with any other situation, having a skillful, enthusiastic team is a big part of achieving your organization’s goals. Communicating the importance of having the ability to learn and stay intellectually flexible is crucial when evolving your SaaS processes. A team that keeps a growth mindset while exercising a strong work ethic will quickly rise through the ranks. Finally, having team members that comprehend the power of storytelling is a big benefit. When interacting with clients or even within the organization, understanding how to sell an idea or weave emotion and meaning into it is a big bonus.

 

Want to learn more about creating SaaS business success? Read our blog Microsoft Tools to Grow Your SaaS Business.