Welcome
Are you getting the full value from your open source usage?
This short self-assessment’s goal is to help identify areas where you could benefit from using a third-party support provider for your enterprise’s growing use of open source software. In July 2019, IBM commissioned Forrester Consulting to evaluate open source usage and the need for support. Using the study data, this assessment will yield customized results and recommendations based on your responses and should take no more than five minutes to complete.
Questions
1. Please select all that apply:
Which of the following classes of open source software tools/frameworks does your team use today?
Questions
2. Please select the best option:
What is the biggest support challenge you face when using open source technologies?
Questions
3. Please indicate your level of agreement with the following statement:
“Our organization lacks a mature governance strategy for open source technologies.”
Questions
4. Please select the option that best matches your current support model:
“What form of open source support do you most often leverage?”
Questions
Recommendation for Question #1
Compared to your peers, the number of open source technologies you are using is relatively low. But the volume of open source technologies doesn’t directly indicate maturity or success.
In our study, we found that:
- Similar to you, 45% of companies are using one to four types of open source software or frameworks.
- However, 55% of enterprises are using five or more types of open source software and frameworks.
Our study revealed that enterprises are dealing with more and more complex data stacks. They are also using open technologies to build mission-critical applications.
Recommendation:
As you expand your use of open technologies, avoid complexity where it’s not necessary. Build a strategy that leverages the advanced technical knowledge of communities and support partners to address complexity challenges early on.
Compared to your peers, the number of open source technologies you are using is on par or higher. Using multiple open source tools can add to the complexity of your technology stack and drive the need for additional support. Enterprises using open source to build mission-critical applications must address challenges around interoperability, security, and skilled personnel.
In our study, we found that:
- 45% of companies are using one to four types of open source software or frameworks.
- Like you, 55% of enterprises are using five or more types of open source software and frameworks.
Recommendations:
As you expand and accelerate your use of open source, look at adopting cutting-edge open source technologies for continuous integration and delivery and function-as-a-service. More advanced offerings open the doors to innovation and to overcome complexity challenges.
Questions
Recommendation for Question #2
You said high security and compliance risk is your top support challenge, and you are not alone. This was the top challenge in our study, with 56% of enterprises selecting it as an open source support challenge.
Be aware of open source risks and the vulnerabilities that continue to plague enterprises as developers rely more on these building blocks to help speed development and delivery. Open source decision makers have no choice but to embrace application security automation and protection technologies. Open source decision makers need to assess the overall risk presented by open source components across all applications, set consistent policies to keep risk to acceptable levels, and work with development teams to guide vulnerability remediation.*
Forrester found developers use open source components to achieve speed; however, vulnerabilities in these components represent a top target for successful external attacks. Embedding software composition analysis tools in the software delivery lifecycle and using the results as a quality gate prevent the use of vulnerable open source while providing developers the speed they demand.**
*Source: “Now Tech: Software Composition Analysis, Q1 2019,” Forrester Research Inc., January 24, 2019.** Source: “The State Of Application Security, 2018,” Forrester Research Inc., January 23, 2018.
You are not alone. The top support challenges faced by enterprise open source decision makers are high security and compliance risk (56%) and interoperability challenges (52%).
Interoperability is a big part of the conversation about open source today. Open source ecosystems in the cloud-native world are rapidly expanding, giving I&O teams access to many applications that can often interoperate with other open source tools in the ecosystem.* As enterprises expand their open source usage, sometimes to hundreds of open source tools and frameworks, interoperability becomes more critical to building mission-critical applications. Enterprises increasingly struggle to know to whom to turn for help with interoperability challenges. A third-party support partner can look across the ecosystem, pinpoint the problem, and get you back up and running.
*Source: “The I&O Pro's Guide To Enterprise Open Source Cloud Adoption, Q1 2018,” Forrester Research Inc., August 31, 2018.You said finding and training personnel that can keep up with technology changes is your top support challenge, and you are not alone. This is among the top challenges in our study with 42% of enterprise decision makers selecting it as an open source support challenge.
Maintaining trained talent can also be difficult in popular open source ecosystems because these skills are highly sought after. For this reason, many enterprises choose remotely managed versions or opt for enterprise distributions — resulting in potentially high costs.*
This skills drought means that even the most competitive companies can’t hire their way out of this problem. Open source decision makers across the globe are turning to resources outside of their organization for help with open technology challenges, such as peer communities and support partners. Peer communities are a well-established resource for enterprises but often fall short in providing real-time support or identifying infrastructure issues. A third-party support partner can support enterprises by filling staffing gaps and offering extensive knowledge of the open source ecosystem and technologies.
*Source: “The Top 10 Facts That Every Tech Leader Should Know About Cloud Standards And Open Source,” Forrester Research Inc., February 2, 2018.It is easy to be overwhelmed by the challenges you face when using open source technologies. We found in our study that the most common challenges enterprises experience are high security and compliance risk (56%) and interoperability challenges (52%). Additionally, 42% of enterprises said finding and training personnel that can keep up with technology changes is a top challenge for them.
Start by addressing the barriers most impacting your progress. If it is security and risk, assess the overall risk presented by open source components across all applications, set consistent policies to keep risk to acceptable levels, and work with development teams to guide vulnerability remediation.*
If you need to overcome interoperability challenges, consider turning to third-party support partner to help you look across the ecosystem, pinpoint the problem, and get you back up and running.
For personnel struggles, most enterprises can’t hire their way out of their skills drought. Open source decision makers across the globe are turning to resources outside of their organization for help, such as peer communities and support partners. Peer communities are a well-established resource for enterprises but often fall short in providing real-time support or identifying infrastructure issues. A third-party support partner can support enterprises by filling staffing gaps and offering extensive knowledge of the open source ecosystem and technologies.
*Source: “Now Tech: Software Composition Analysis, Q1 2019.Questions
Recommendation for Question #3
You indicated that your organization does not have a mature governance strategy for your open technologies. That’s OK: 64% of the enterprises in our study also struggle with governance.
A third-party support partner could be a big help here. Other enterprises that do not have a mature governance strategy are experiencing other challenges like real-time support (63%), interoperability between open source technologies (55%), and minimizing risk (43%).
Forrester has found that without governance, you will accumulate unmanageable technical debt. We recommend you ask the hard questions before you invest millions in building with new tools that may not have the support you need in the future. Balancing these concerns with your product team’s desire to innovate is one of the hardest challenges facing the modern digital manager.* Support partners can help you achieve that balance and develop a governance strategy that meets your needs.
*Source: “The I&O Pro's Guide To Enterprise Open Source Cloud Adoption, Q1 2018,” Forrester Research Inc., August 31, 2018.Congratulations! You stand out from most of the enterprises in our study. Only 20% said they have a mature governance strategy for their open source technology.
A mature governance strategy can be instrumental in avoiding accumulation of unmanageable technical debt. However, we found in our study that even enterprises that have a mature governance strategy for their open technologies have potentially serious challenges elsewhere. Eighty-nine percent struggle to minimize the risk associated with open source adoption, 87% struggle with real-time support for open source, and 80% struggle with interoperability between open source technologies. Leveraging support partners can help you continue the good work your organization is already doing.
Questions
Recommendation for Question #4
Your score means that your open source support model doesn’t rely on dedicated open source partners or peer-to-peer communities.
There are helpful resources that can help improve your open source strategy and usage. Here are some recommended steps to further you along your journey:
- Find peer-to-peer communities to be involved in. This is an important element of support and inspiration for your open source software.
- Look into options for working with a third-party dedicated support service. This is where you will find extensive support for a single open source technology or across stacks. See our study to learn more about what a dedicated support partner can offer.
Your score means you are relying on peer-to-peer communities for open source support. You are in good company: 57% of the enterprises in the study are also leveraging peer-to-peer communities.
- Active participation in open source communities can help with problem solving, but they can fall short in identifying infrastructure issues, real-time support, and interoperability issues.
We found that 53% of enterprises are not aware that third-party support exists for their open source software.
- Since you are currently not using third-party support, you may be in that group.
- Third-party support services can provide support in the areas that enterprises have identified that communities fall short.
Recommendations:
- Think about increasing your participation in peer-to-peer communities. You can demonstrate your thought leadership by donating code or projects back into the communities from which you seek support.
- Leveraging communities can level up skill, provide insights through workshops, and more.
Your score means you are using a dedicated support partner for one or more open source technologies. Congratulations! You are thinking about open source in a more advanced way than many of your peers. We found that 53% of open source users are of not aware third-party support partners are available to help them tackle the complexities of a growing technology stack.
If you are currently leveraging a dedicated support partner for a single open source technology:
- Consider looking into (a) partner(s) that can support you across your multiple open source software types. Support partners can provide an agnostic view of your IT strategy to ensure you pick the optimal technologies to meet your goals and needs.
If you are currently leveraging a dedicated support partner across multiple open source technologies, you are in a small but more advanced group:
- We found that only 21% of the enterprises in the study are using a support partner across multiple open source technologies.
- Ensure that your support partner is not only supporting you across multiple technologies, but across multiple initiatives. See our study to learn more about the support features you may be missing out on.
Thank you for taking the assessment.
Beginner
Your score means you are most likely just beginning to scale AI and ML at your organization. Now is the time to make AI and ML a priority for your data and analytics investments: 80% of firms that are advanced with their AI/ML readiness say that AI and ML will be the most important factor in their business competitiveness in three years. While your data science team is likely small, here are some tactical recommendations to drive business value and get the most out of your initial AI and ML investments.
- Create a data science center of excellence. A center of excellence helps to democratize AI and ML in your organization and standardizes data practices to help get more high-quality models into production. Fifty-one percent of your intermediate and 71% of your advanced competitors have already implemented or are expanding their COE, while just 19% of your beginner peers have done so. Creating a COE is the fastest way to get your AI/ML practice off the ground.
- Encourage cooperation between data science, IT, and the business. Critical to success moving AI into the business is to foster collaboration and trust between your data science team building and implementing AI/ML models and the users trying to take those data insights and implement changes in the business. Nearly half of your intermediate competitors and two-thirds of advanced firms are undertaking initiatives to encourage cooperation between these often-siloed groups.
- Democratize AI and ML with automated machine learning and easy-to-use platforms. Most of your beginner peers have already made initial investments into machine learning and customer analytics platforms, so if you have not, that should be your first step. The next step many are taking is investing in automation platforms for ML. Automation is especially important to smaller data science teams because it allows data workers to easily create and implement new models and increases the productivity of your limited data science resources.
- Invest in technology to close the insights-to-action gap. The stage of the AI to ML lifecycle where your beginner peers encounter by far the most challenges is turning the insights from AL/ML initiatives into actionable changes to the business. To help close this insights-to-action gap, your more advanced competitors are increasing investment in new technologies like decision management and optimization and simulation solutions to find the best combination of business actions based on inputs from AI and ML models.
Intermediate
Your score means you are well underway with scaling AI and ML to drive business value at your organization. You are likely still growing your data science talent, so here are some tactical recommendations to drive business value and get the most out of your initial AI and ML investments.
- Focus on expanding business use cases. As you scale AI and ML into different areas of the business, elevate your use cases from those focused on driving efficiency to those driving business value. Your more advanced competitors are focused on use cases that improve the customer experience they can deliver, improve strategic decision making, and develop new revenue streams.
- Invest in technology to close the insights-to-action gap. To help close the insights-to-action gap, your more advanced competitors are increasing investment in new technologies like decision management and optimization and simulation solutions to find the best combination of business actions based on inputs from AI and ML models.
- Invest in ModelOps solutions to overcome model development and maintenance challenges. Your AI/ML projects may be underperforming due to challenges maintaining those models to ensure their accuracy. Your intermediate peers say model development and maintenance is the most difficult phase of the AI/ML lifecycle. ML operations solutions are designed to help both accelerate the deployment of AI and ML models and monitor them in production, making it easier to retrain them when conditions change.
- Expand your data collaboration initiatives. Advanced AI/ML firms further expand and democratize AI by creating data science centers of excellence and undertaking initiatives designed to foster collaboration both within your analytics teams and across the business and IT. Sixty-nine percent of your advanced competitors have already implemented or are expanding their COE, so if you do not have one, this is the time to act.
Advanced
Congratulations, your score means that your AI and ML practice is thriving today. You are ahead of the curve on scaling AI and ML through your organization and driving business value with your initiatives. This is no time to rest on your laurels, however. Your advanced peers believe AI and ML is the most important factor to being competitive in the future and are investing with this mindset: 60% of your peers say they will invest at least $5M in AI/ML platforms in the next year. To continue to grow your practice effectively and improve your business results you should:
- Expand AI’s influence and boost productivity with automation. Tools like autoAI can help turn data workers into de facto data scientists with capabilities that automate feature engineering, model selection, parameter tuning, and model deployment. Your advanced peers see automation for AI and ML as by far the most valuable features of AI/ML platforms. These features not only allow data workers to quickly and easily develop AI/ML models but lets your precious data science resources work more productively and work on higher-value use cases.
- Drive trust in AI with governance and transparency. Drive trust and reduce risk while also improving business outcomes by investing in solutions for tracking model lineage, monitoring your models for data drift, and declining accuracy, as well as new techniques for providing explainability, bias detection, and mitigation features. This is another top feature for advanced firms to get the most value from their AI/ML platforms.
- Invest in ModelOps solutions to manage models at scale. Implement platforms with ModelOps capabilities that enable you to take models developed across a wide range of ML tools and frameworks, rapidly deploy them across hybrid environments (on-premises, private cloud, and multiple public clouds), retrain, and redeploy models as part of a continuous improvement process.
View your detailed results
Next Steps
Want more information?
Ú Engage an IBM expert to learn how IBM can help you get where you need to be with open source or download the full study.
Ú Read the eBook, "Support Solutions For The Open Source Environment" to learn ways to manage the increased complexity of your open source software ecosystem.
Ú Watch our webinar that includes key data from the Forrester Commissioned Study to learn more about open source support solutions and overcoming challenges in open source environments.
Methodology, Disclaimers and Disclosures
Methodology, Disclaimers and Disclosures
Methodology
Methodology
In this study, Forrester conducted an online survey of 263 decision makers in the Canada, the US, the UK, Denmark, Spain, Italy, France, Russia, Germany, Australia, China, Japan, South Kora, and New Zealand to evaluate the current state of their technology and operational strategies. The study was completed in September 2019.
Disclaimers
Although great care has been taken to ensure the accuracy and completeness of this assessment, IBM and Forrester are unable to accept any legal responsibility for any actions taken on the basis of the information contained herein.
Disclosures
This interactive tool is commissioned by IBM and delivered by Forrester Consulting.