Data & Intelligence

Business Intelligence – Implementation Challenges

Business Intelligence should help organizations improve business outcomes by making informed decisions. The problem is that Business Intelligence is the overarching term applied to the tools, technologies, and best practices that that supposedly help organizations make sense of data. Where should you start? What tools should you use? What are the best practices? How do you manage the mass of data flowing into your organization? To which buzzwords should you pay attention? Perficient’s Enterprise Information Solutions group helps organizations determine how to put business and intelligence back into Business Intelligence.

In previous posts, I looked at Business Intelligence and what it means today and Business Intelligence – Future trends. In this post, I look at implementation challenges and how they might be addressed. The current state of business intelligence and the future trends, present a significant set of challenges to organizations trying to improve and leverage the data they have. Perficient’s Enterprise Information Solutions Company Wide Practice helps organizations do just that. The challenges that organizations face fall into a number of key areas.

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In many Business Intelligence environments, a big challenge faced has nothing to do with technology but is to do with the organization itself. How does the organization enable cross organization collaboration? How are business sponsors recruited and engaged? How is dedicated business representation aligned and maintained? How is the focus on the top priorities established and preserved throughout? What is the right team and how is it put in place? Enterprise Information Management (EIM) Strategy Sessions help organizations achieve confidence in the data and information they produce and use it to improve top-line performance. The EIM Strategy Sessions should drive out the following actions in order to prepare for future success.

  • Developing and aligning the vision with the business’ mission, goals and priorities
  • Mapping business drivers to analytical needs and capabilities
  • Identifying opportunities for creating new business value
  • Documenting the common themes of business pain and obstacles, and identifying comprehensive solutions
  • Assessing organizational and technical readiness
  • Generating a business-driven roadmap
  • Clarifying and communicating the strategic direction, and establishing a program sponsor
  • Establishing the initial return on investment justification

Once an organization understands what they want Business Intelligence to provide, the next challenges become more technical. How should they manage the exploding user base? How should the increasing volumes of data be handled? How should all the new and different types of data be controlled? How should the integration of new data sources be controlled? Central to managing these items is a solid, well-planned architectural foundation. Many Business Intelligence environments have evolved organically but they typically cannot advance beyond a certain point. What is needed to establish a platform the will perform, scale, and adapt to future needs is a Foundational Solution Architecture design. The process to establish this includes:

  • Creation of a conceptual model that supports the business needs and objectives mapping business requirements to architectural capabilities
  • Mapping current capabilities to the conceptual model identifying gaps to be addressed and filled
  • Specifying a best practice based architectural solution that will address organization’s business needs and requirements
  • Mapping application components onto the platforms and infrastructure systems to create a complete solution architecture
  • Identify the key entities, tools, and technologies needed for initial delivery phases and the minimum value set
  • Adding detail to the return on investment plans in order to justify moving forward

The strategic objectives and tactical components identified lead to the next hurdles for an organization to face. How should cost be controlled in order to meet the return on investment justification? How can business value be created quickly? How can target delivery dates be guaranteed? How should shifting priorities and business needs be managed? The best way to meet these challenges is to establish a formal Business Intelligence Program. The program can leverage centers of excellence for data governance, information deliver, and such, or it can be fully contained and manage the whole process. The Business Intelligence Program should:

  • Stand up program governance by establishing a program governance team, protocols, and charter
  • Build a high-level, iteration-based program plan based on priorities, ease of implementation, and time to value
  • Determine scope, deliverables, and success criteria for each iteration
  • Determine the detailed plan, resource requirements, and costs for the initial and subsequent iteration
  • Communicate the plans and gain approval to move into the implementation phase

Once the key initiatives identify and plans in place, it is time for the organization to translate strategy into action. Implementation should follow an organizations typical implementation cycle whether that is waterfall, agile, or hybrid. The methodology should be rigorous, planned, and monitored. It should include the following activities:

  • Project management and progress reporting
  • Detailed solution design
  • Database, data warehouse, data mart implementation
  • Data integration, data cleansing, data transformation services
  • Extract, Transform and Load (ETL), Report, and Dashboard development
  • Predictive model development
  • Testing
  • End-user training, coaching, enablement, and support
  • Support-staff training and mentoring

Perficient’s Enterprise Information Solutions Company Wide Practice helps organizations identify and tackle all of the areas discussed above. We apply a business focused, technology agnostic approach to help organizations rapidly realize business value.

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