Historically, data and analytics service projects have been predominantly, technology-related with most projects being, data management, and analytics, and business intelligence, technology implementation efforts. Today however, digital business and the need for analytics is increasingly disrupting every industry. It's ignited a sense of urgency among business and IT leaders to use data and analytics to support the digital transformation, other organizations with essential insights about their customers, partners, employees and things. Meanwhile, the abundance of data and the increasing complexity of data sources, technology and analytic methods to service the rapidly evolving business demands, have prompted many organizations to realize the need for additional support from an external service provider. Today, projects are more holistic and require a wide set of skills. These skills range from data and analytics technology implementations, to manage services on platforms, to deliver various business and operational analytics, as well as strategic advisory services to enable a data-driven organization that leverages innovation in artificial intelligence. As a result, selecting the right service provider or consulting firm is becoming more complicated. There are six critical capabilities that differentiate data and analytics service providers. The first is Business Process Consulting. Business Process Consulting focuses on specific industries or processes to redesign the way work is done. These consulting capabilities are specific to an industry or business process that may also include frameworks, best practices and templates to identify, analyze, and redesign business processes to improve critical performance measures such as cost, quality, service and speed. The next skill is Business Change Management. This is the provider's ability to understand the changes needed within the business operations and to help clients change or transform its organization and adopt data and analytics solutions optimally. Next is a Design-Lead Approach. This is the provider's ability to design and implement data and analytics solutions that can effectively drive the consumption of data throughout the client's organization and to make the impact sustainable. A Design-Led Approach refers to the multidisciplinary competencies of creative design, innovation, analytics, security and technology integration. It may also require the provider to adopt digital agency capabilities to extend its technology integration capabilities. Some providers offer Managed D&A as a Service. This refers to the provider's ability to embed intelligent automation in platform based data and analytics solutions in a public or managed cloud environment. Managed D&A or D&A as a Service requires additional capabilities including the frequency and quality of insights that can be delivered to the clients as a service, as well as helping clients reduce upfront costs and free up resources to contribute more value-added activities. Another differentiator is what's called Asset+ Consulting. This refers to the providers effectiveness in using intellectual property assets to augment existing insight and expertise for a particular vertical industries or to provide analytic insights to address complex problems. These assets may include embedded artificial intelligence and machine learning technologies in data and analytics platforms, various kinds of tools, accelerators, or algorithms to improve the decision-making process and the accuracy of business outcomes. The last differentiator is Technology Enablement. This is the provider's ability to educate, ideate, evaluate, and implement new and existing analytics solutions and technologies including AI, in the most optimal manner within an existing environment to support business requirements. Technology Enablement capabilities include investments in new analytics technologies, tools and reusable assets, as well as capabilities and solutions in project delivery. Analytic service providers tend to focus on four types of use cases. The first is strategy and consulting. This includes advisory services that focus on developing, data and analytic vision, strategies, approaches, designs or architectures but in which a solution implementation is excluded from the project. These advisory service projects are often a key component of the digital business transformation strategies and depict journey maps and roadmaps to achieve these transformations. They're often business consulting initiated and strategy initiated, and are focused on how to improve the efficiency and accuracy of the business outcomes. While the projects don't extend into the implementation and deployment of solutions, they may include a Proof of Concept or POC with deliverables to understand and envision the potential outcomes. Then there are Analytics Implementations. This is the implementation of indoor services provided on an ongoing basis, on a traditional analytics platform or modern platforms and analytic applications. Then on the flip side, there are Data Management Implementations. This is the implementation and are services provided on an ongoing basis on solutions that describe, organize, integrate, share and govern data in one or multiple management systems. Data management solution services include specific optimization strategies designed to support analytical processing. Then finally, there are Data Science and Machine Learning Implementations. These are services provided on an ongoing basis and advanced analytic technologies. These kinds of services and technologies offer a mixture of basic building blocks essential for creating all kinds of data science solutions.
