Data Analytics Strategy
Start Analytics with the Right Strategy
The Importance of Strategy:
Analytics initiatives often fail because they do not deliver the promised results to support the top strategic goals of an organization. Enterprise-wide analytics cannot be implemented with a project driven point solutions mindset, it’s effects are far reaching and must be implemented differently.
Primary execution capabilities in organizations are developed over time around their core business operations. The combination of business, technology and quantitative skills needed for developing a mature analytics capability are not often internally available. That is where we can help.
Our Strategy Engagement
We recommend starting business analytics initiatives with a strategy engagement. We meet with your team to understand what your company is trying to achieve in the next few years, clearly define what business results you are trying to achieve, and determine what stands in the way of accomplishing these goals.
A typical strategy engagement covers five key areas related to analytics. These areas allow for a complete assessment and actionable roadmap to be created.
We foster business and IT collaboration by developing a comprehensive roadmap, creating a business case for securing investment, hiring, and retaining the talent to sustain the capability, and managing the organizational change required to drive innovation and adoption of analytics. The task of effectively implementing an enterprise-wide data analytics capability often turns out to be a very challenging endeavor. Typical deliverables of a strategy engagement include the data management strategy, technology platform architecture, organization and staffing strategy, quantifiable analytical use cases to measure the business impact and the level of innovation and organizational change required.
Analytic success is only as strong as the people involved. In order for your analytic strategy to maximize potential, you need the right people involved to implement it consistently. It is our job to assemble the best people to carry out the strategy, train them, and follow through. Consistency is key- if everyone involved, from the CEO, managers and technologists, have a common language and open line of communication, executing your plan happens naturally.
First, we help to develop your analytics vision and set target analytics maturity levels by figuring out your current and target maturity levels. Together we decide on organization and capability development and organize your talent pool to the right size and mix to execute plans and implement your target architecture. We then recommend how to outline how your organization can nurture data scientists, analytic modelers, and frontline staff who can continue analytics and data-driven decision-making processes. Your finished analytics strategy will provide a common language, allowing IT professionals, data scientists, and managers to discuss where the greatest returns come from, and select where to get started. After that the execution of your plan becomes easier. Data integration, initiation of pilot projects, and the creation of new tools and training efforts will form a clear vision for driving business value. Our refined process will help you understand the specific business challenges you wish to address, identify the main elements of your solution, pinpoint risks related to the proposed solution. Finally, we help to prioritize your initiatives to form a clear plan that leads to success with our support.
Assembling and integrating data is essential. Companies are buried in information that’s frequently siloed horizontally across business units or vertically by function. Critical data may reside in legacy IT systems that have taken hold in areas such as customer service, pricing, and supply chains. Complicating matters is a new twist: critical information often resides outside companies, in unstructured forms such as social-network conversations. Integrating data alone does not generate value. Advanced analytic models are needed to enable data-driven optimization (for example, of employee schedules or shipping networks) or predictions. A plan must identify where models will create additional business value, who will need to use them.
Although you may not consider technology in the form of in-memory analytics very exciting, you do care about having the ability to quickly and instinctively analyze data. Leave it to our IT professionals to create a pristine analytic structure that will correspond with your business outcomes. Your existing IT structures may not support new data storage and analysis, it is our job to efficiently synch the most important data for analytics so we can get started right away.
A few of the outputs of a strategy engagement
Use Case Development
Creation of use case based interviews where cases are clustered by theme and then prioritized. We deliver the prioritized list with the benefits of each use case.
Business Process Maps
First we interview business SMEs and discuss workflow with regards to data. We document and create a process map and validate with business functions. We will then deliver business process flow maps of each business unit.
Data Requirements for Analytics
We get data for prioritized use cases and identify data required to satisfy each use case. These data requirements for each case will be shared with the company.
Analytics Platform Architecture
After understanding current architecture and capabilities, and developing an overall architecture to support the analytics road map we create a platform architecture diagram depicting all aspects of an enterprise wide platform for supportive analytics.
A complete strategy engagement can consist of as many as 24 different work packages. Each is strategically designed to address a specific aspect of implementing enterprise-wide analytics.
We want to work with you!
Overwhelmed with data or want to test out analytics.
Then we’d love to talk to you about your business.