Platform Convergence, Analytics, and Mobility Drives Disruptive Business Models in Government
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Platform Convergence, Analytics, and Mobility Drives Disruptive Business Models in Government

Niten Malik, Director, US Public Service, Microsoft
Niten Malik, Director, US Public Service, Microsoft

Niten Malik, Director, US Public Service, Microsoft

The efforts to build sophisticated cloud or on premises solutions are often complicated by inflexible technology.

These days, no organization can afford to spend millions of dollars or take decades to build and maintain even complex systems, especially cash-strapped government agencies. Government business processes are complex and often unique. They must typically meet multiple competing objectives such as balancing national security, privacy or budget constraints, changes in legislation and levels of customer service.

The systems developed to meet these requirements are often difficult to maintain and costly to change. It is costly for the business to keep pace with technology innovations. This is especially true when the underlying application development platform requires customization to take advantage of technology innovations to improve its own mission. The predominant strategy for developing systems has been custom code or by modifying traditional Enterprise Resource Planning (ERP) packages.

However, aligning government business processes to rigidly defined out-of-the-box ERP workflows has proven expensive and time-consuming. Often, it’s a profound challenge to adapt traditional ERP process flows initially developed for commercial business to the government’s unique business requirements. Lack of flexibility and the high cost of customizing proprietary work-flows impede innovation and limits business processes from being optimized.

To compensate for the lack of process flexibility and more closely align system capabilities to government requirements, agencies often rely on custom code. However, this is costly and time-consuming to develop and maintain. A stable of programmers creating often millions of lines of code raise the level of difficulty. Enforcing methodology, inadequate documentation, and dependence on programmers who alone understand what they’ve coded slow the pace of innovation. At the end, responsive technology architecture is elusive at best.

Get off the Shelf

The challenge facing government programs is reducing cost and adapting to change. The business case must hinge equally on cost savings and mission reliability.

Dynamics CRM is the next generation solution-development platform. While it enables unique requirements to be built in a non-proprietary language, it also offers a comprehensive set of configurable capabilities and architecture components such as security, data access, workflow, and presentation logic out of the box. This limits custom development to the system’s most unique functions. Custom coding less of the required functionality from scratch reduces development and O&M cost significantly. It allows for quick implementation of requirements, thereby enabling an abbreviated change governance process, agile application development, and responsive business processes. Dynamics CRM provides a reliable framework for not only extending and scaling applications but also building multiple applications on the same platform.

Fewer steps to input and retrieve information enable mobility and higher data accuracy. Solutions should use convergence of different platforms such as Share Point, Dynamics CRM, Lync, and email to help users move reliably and efficiently through the process. Further, data processing should be enabled on a range of mobile devices without additional custom development.

Innovate Every Day and “Social BPO”

Few things are more certain to slow the pace of innovation than having to wait for the next software release cycle. Innovation must be iterative and ongoing in a user-centric organization. Interface changes or business-logic updates must be accomplished in hours or days, not weeks or months.

Tools like Dynamics CRM are easy to learn, thereby giving business users a hands-on engagement in building business applications, or themselves implementing new ideas. The culture of innovation within the organization drives motivation especially within next generation workforce.

Importantly, the pace at which technological advancements are incorporated in the platform itself will influence how future capabilities are available to users of the applications built on the platform. Tools like Dynamics, Azure (Microsoft Cloud), and O365 have significant R&D commitment so they continuously bring future innovation to users.

Convergence of line of business applications with tools like Share Point, email, IM drive productivity and organizational change. In a typical case management process, adjudicators often need to consult on eligibility questions and create escalations. This creates unpredictable delay in case resolution. A “social” Business Process Operations (BPO) leverages the convergence of eligibility workflow and collaboration tools such as Lync, Yammer, or Share Point for real-time problem solving.

Dealing Big Data

Agency’s core mission depends on the reliability and speed at which you can share and analyze data from many sources. Even more important is to “democratize analytics” by making powerful analytics tools, (i.e. Azure HDInsight to deploy and provision Hadoop clusters in the cloud or Power BI for Office 365 to analyze and visualize data), affordable, scalable, and widely accessible to business users.

You’ll have to harness Big Data to create mission specific decision technologies. Higher-quality decision making based on deeper insight into data leads to proactive response to risks and opportunities. Assimilating data from external sources and correlating it with internal databases gives programs systematic visibility into external factors that impact their mission. Threats to a program’s mission aren’t static. Predictive analysis systematically looks for trends and anomalies within internal and external data including contextual information that draws relevance from social data.

“Solutions that natively integrate workflow, collaboration, and analytics tools; offer secure cloud deployment options”

Azure Machine Learning, a cloud service for implementing predictive analytics, leverages advanced algorithms and the nearly unlimited scale of cloud storage and compute to teach computers to use historical data to predict future behavior. Even when we have “connected the dots”, we often lack a reliably systematic response management and decision making capacity. Therefore risk mitigation and accountability depends on making data insights actionable through convergence with Dynamic CRM work flows that trigger reliable response management and data sharing across multiple wings of the Government and military for reliable and fact based decision making.

Cloud and On-Premises Architecture

Solutions will operate in the cloud to optimize cost and improve reliability. Differing business needs mean a single cloud strategy won’t be applicable to all programs. Some applications won’t be deployable on a public or government cloud, while others might leverage only certain cloud capabilities.

System Center provides multiple cloud-enabled developments and service-delivery models that take into account each program’s unique security and operating requirements. It also provides the flexibility to deploy solutions across multiple types of cloud infrastructures (private cloud, government community cloud and public cloud) as security constrains and technology evolves. Azure provides infrastructure, platform, and software services that enable rapid deployment of services at scale and can also support federation between cloud environments. For example, Azure Active Directory (AD) provides an identity federation solution that supports on-premises AD as well as public and government clouds from Microsoft and other companies.


Solutions that natively integrate workflow, collaboration, and analytics tools; offer secure cloud deployment options; and bring data processing to mobile devices have the potential to drive disruptive operating models.

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