Machine learning (ML), Artificial intelligence (KI), Blockchain and the Internet of Things (IoT) are currently some of the most interesting technologies for companies. According to a study by the digital association Bitkom from spring 2019, the companies surveyed believe that these are relevant to their competitiveness.
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Anyone who determines at any time what their customers’ ideas and expectations are, can tailor their offers and services accordingly. The analysis of machine data in connection with AI and machine learning models allows a provider of machine tools to offer additional services such as proactive maintenance.
However, very few machine builders or retailers have the resources to develop corresponding applications themselves. This is especially true for small and medium-sized companies. This is where Independent Software Vendors (ISVs) come into play. You can enrich your solutions with analytics functions and offer your customers added value.
But even for an ISV, the question arises: “Buy it or develop it yourself?” And in many cases the answer is likely to be the same as for your customers: Instead of developing analysis tools and machine learning algorithms yourself and integrating them into your software, you can obtain such functions as a service from the cloud and combine them with your own software. Because cloud service providers provide the relevant interfaces for their analytics solutions. Software vendors who use a do-it-yourself approach take risks. These include hidden costs, increased implementation effort and possibly problems with scalability and support.
According to the IDC study “Critical Factors and Trends in Analytics for Independent Software Vendors”, 68 percent of ISVs work with providers of cloud-based big data and analysis services. For a software house, this can pay off in several ways. For example, it has the option of using integration options that also include infrastructure services from the provider. In addition, a number of cloud providers support ISVs in the form of technical support, training and go-to-market strategies. In addition, the cooperation results in cross and upsell options for a software provider. If renowned providers are involved, an ISV also benefits from their technical expertise and good name.
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The customers of an ISV also benefit if they combine such analytics solutions with their own offers. According to the study, 70 percent of ISV customers said that using analytics has improved the way they work with their own customers and other stakeholders. 56 percent each cite improved decision-making processes and the opportunity to stand out from the competition through innovations as additional advantages. In turn, almost two thirds (63 percent) of software providers were able to develop new business models if they shared data analyzes with their customers.
In order for such successes to materialize, it is necessary in advance to find the right cloud service provider who provides big data and analytics-as-a-service. The following questions can serve as a guide:
Does the analysis solution fit the application? This often does not have to and often cannot be the case one hundred percent. However, the solution should meet the majority of the requirements.
Are there any special requirements to be observed? This could be, for example, high transaction volumes or the requirement that the cloud service must work with other systems in real time. The connection of IoT components such as sensors to machines, vehicles and measuring systems must also be taken into account.
Does the provider or its partner have experts who can help with the implementation and integration of the analysis solution? ISVs should also review support services and the associated costs.
Are there technological dependencies between the analysis functions and other components of the infrastructure?
What about the scalability of the analysis software and the IT resources of the cloud service provider? Because the provider must be able to provide its service even if the number of customers of an ISV who use the analysis solution increases dramatically. In this way, the access times must not suffer when there is a high demand for the cloud service.
What does it cost? A total cost of ownership (.TCO) analysis of the analytics solution is helpful here.
Another question concerns data security: Where are the servers located and which data protection standards does the provider meet?
According to the IDG study, the General Data Protection Regulation (GDPR) „Cloud Security 2019“ Research clearly influences decisions when choosing cloud providers. The location of the data center in Germany can be a decisive factor when choosing a provider. Cloud certificates and data protection certifications can also provide an overview of the existing security standards.
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If an ISV receives satisfactory answers to these questions and the necessary security criteria are met, nothing stands in the way of working with the provider. Software providers in particular who want to expand into other regions should check how the provider’s cloud infrastructure and services are doing. If a provider already has appropriate cloud data centers and internet access points there, an ISV can also offer its solution there in combination with the analytics solution.