ENTERPRISE ANALYTICS FOR ROAD MAP

Accuracy Business Analytics road map consists of steps depicted in the above diagram which involves processes and activities designed to obtain and evaluate data to extract useful information.

1) Consulting

Accuracy have been helping customers in their Analytics roadmap, beginning with consulting, discovery and the purchase of tools that provide exploratory analysis capabilities.Over time, exploratory techniques typically evolve to more automated and repeatable processes, which then increase the effectiveness of the analysis.

2) Exploratory Data Analysis

Exploration is a one-use process—a starting point that may be used to help identify patterns or potential risk areas within a business system. It is typically used for an initial investigation as a way to begin to understand the business processes while becoming familiar with the data. The effort to develop and document exploratory is time well spent because that information may be used going forward to automate the process for repeatable results

3) Repeatable

The use of exploration often requires an enterprise to rely on selected skilled individuals to perform the testing; such reliance may increase risk, due to attrition and the lack of knowledge transfer. In addition, enterprises that have seen the benefits of Analytics tend to begin to look for ways to improve the efficiency and increase the frequency of running analytics.
For these reason, exploration inevitably leads to the next maturity stage: repeatable Analytics. Repeatable Analytics is predefined and scripted; it is designed to perform the same tests on similar data (e.g., data from a different time period) on a scheduled basis. The benefits include consistency, efficiency and more effective corrective actions. Analytics are often stored on the personal workstations of analysts or analytic “librarians.” These program scripts become members of logic libraries that can be run repeatedly, used for training purposes or used as the basis for new Analytics projects. The quality of analysis is improved and remains consistent from run to run, as the data acquisition process is partially or fully automated.

4) Centralised

The next step up the maturity scale from repeatable Analytics is a centralised approach for the development, storage and operation of repeatable Analytics. In this approach, a central repository is established for repeatable Analytics programs and standard data files; standards for Analytics development are documented and Analytics applications are set up and scheduled to run against the centralised data on a regular basis or on demand.Data to be analysed may either be pushed to the repository or extracted directly from different sources as needed, and the analytic results themselves are stored in the repository.

5) Continuous Monitoring

Continuous or actionable intelligence marks the highest point on the maturity scale. At this stage, analytics are fully automated and running at regularly scheduled intervals and may be embedded directly into a production system. A continuous run of analytics enables the immediate identification of potential exception transactions.
Continuous monitoring would allow actionable intelligence and would include sophisticated web interfaces, e-mail notifications, workflows, remediation tracking, dashboards and/or heat maps. The benefits to the enterprise include improved efficiency, reduced errors and timely identification of problems.
As organisations face increasing levels of competitive pressures, decisions need to be made faster than ever. An analytics solution well implemented can help organisations to avoid any lost opportunities and uninformed decisions.