Framework for Report Rationalization

By Subhradip Kar

Synopsis

Companies are continuously striving to democratize data and leverage data optimally for decision-making. Actionable insights derived from data can help companies differentiate and win in the market. Reports are a key mechanism through which business users consume insights to make important decisions. However, over time, organizations tend to produce and accumulate a huge number of reports that makes it counter-productive and extremely challenging to glean accurate insights for decision-making.

Business users drown in a deluge of information that defeats the core purpose of such reports. Additionally in most organizations, there are multiple BI tools with overlapping capabilities that deliver these reports that pose its own set of challenges.

To remediate these challenges, it is imperative to define a strategy for report rationalization and adopt a structured approach towards rationalizing reports across different business units and functions. While the reporting environment is streamlined, the ultimate focus should be on establishing a modernized nextgen reporting environment that offers many benefits to the organization. This whitepaper covers details around how such strategies should be defined and proposes a structured framework for approaching the report rationalization initiative.

Industry Background – Impact of Data & Insights

In today’s competitive and fast-paced digital environment, companies try to differentiate by focusing on five (5) core themes:

  • Driving Customer Centricity – amplify data driven personalization to augment customer experiences, consistent and contextual experiences across channels and data acting on personas by pushing insights in real time
  • Improving Efficiency and Reducing Cost – automation and process improvement, reduce technology debt, data engineering excellence & establishing advanced data platforms to integrate all types of data and drive insights
  • Innovating to establish New Revenue Streams – differentiated products and services, partnerships to augment niche capabilities and marketplaces to collaborate across ecosystems for monetizing data
  • Better Managing Risk – stronger data governance policies and controls, flexible platforms to embrace and address evolving regulations
  • Transforming Operating Models – promote seamless Business – IT alignment, Agile and DevOps based delivery models

A common denominator driving each of these themes to deliver value is “insights” that power data driven decisions.

Diagram-1-Data-Driven

                                                                               Diagram 1 – Data-Driven Decision Making Value Stream

There are different data consumption patterns that enable “insights” such as Interactive Reporting and Data Visualization, Data Discovery and Exploration, Advanced Analytics, Search, etc. Among these different patterns, one that has been around for a very long time and that will continue to play a significant role in the foreseeable future as well is Reporting. That said the typical challenge that most companies face with reports is a “problem of plenty” i.e. a plethora of reports that are difficult to manage and offer inconsistent insights hampering rather than aiding decision making.

Business Need for Report Rationalization

Companies need to transform into “insights driven organizations” so that they are able to create an impact on each of the five core themes to differentiate in their industry and outperform their competitors. However, most companies are struggling to effectively democratize data and deliver insights thereby impeding their progress towards transforming into an insight driven organization. There are many challenges that companies need to be able to overcome in this transformation journey:

  • Data Engineering – data deluge, newage data, varied integration patterns, etc adds complexity to data ecosystems
  • Technology Debt – legacy data estate and tooling creates roadblock for enabling new age data consumption
  • Redundancy – replication of data, models, reports, etc across business units with lack of reuse creates inefficiency
  • Usability – deluge of reports, different personas, lack of self-service and data exploration capabilities hinders usability and decision making
  • Data Governance – lack of visibility into data quality, lineage, metadata, etc hinders usability and trust in data
  • Data Security – fine-grained security and access controls on data at rest and in motion, PII data protection, etc are imperative to secure and manage data privacy
  • Cost of Operations – higher cost of operations due to ineffective integration, lack of modularized DevOps processes, etc

While it is important to mitigate against each of these challenges, we will focus on defining an approach for resolving the redundancy and usability challenge with reports. Most mid to large sized companies today have hundreds and thousands of reports across different business units and functions. These reports often provide inconsistent metrics and KPIs that dilutes trust in the data and impedes the decision-making process. Lack of adequate governance around the KPIs and reports further exacerbates the problem leading to redundancy and duplication across reports. Most companies also end up owning multiple Business Intelligence (BI) technologies with overlapping capabilities to deliver these reports. All of this leads to increased effort for managing and delivering reports, reduced efficiency, lower user adoption and higher total cost of ownership (TCO).

There is an urgent need to rationalize and streamline the existing reporting landscape and migrate to a modernized nextgen reporting ecosystem.

Approach for Report Rationalization

There are primarily two strategies to consider for report rationalization and migration:

Strategy 1 – Migrate first and Rationalize later

Strategy 2 – Rationalize first and Migrate later

Diagram-2-Report-Rationalization.png

Diagram 2 - Report Rationalization and Migration Strategies

Each situation being unique needs to be assessed thoroughly prior to finalizing a particular strategy. There are a number of factors to consider before a specific strategy can be chosen:

  • Existing TCO, business case for report rationalization and migration and associated ROI plan
  • Number of reports and relative report complexity in the current state environment
  • Level of complexity involved in migrating reports to the new reporting platform
  • Severity of technology debt with the existing reporting platform
  • Level of business engagement anticipated and associated business commitment
  • Dependencies based on other key company-wide initiatives

Irrespective of the strategy chosen, which determines when in the process the rationalization of reports happen, we must adopt a structured approach for analyzing the existing reports and determining the report transformation strategy. A holistic approach for report rationalization needs to consider both a “technical” and a “functional” assessment of the current state reports to determine the suggested report disposition for the target state.

Diagram-3-Report-Rationalization-1

                                                                                         Diagram 3 – Report Rationalization Approach

Technical assessment of large reporting environments with hundreds and thousands of reports can be a daunting undertaking that can consume a lot of effort if planned manually. The better approach is to automate part of the technical assessment using accelerators that can consume and understand report metadata and use this metadata to compare reports in order to determine percentage of overlap. Such accelerators can allow reports that need to be compared to be grouped by various parameters e.g. by data sources, by functional areas, by semantic layers and by choosing specific set of reports. Such co-relation and overlap analysis can help segregate reports into different rationalization scenarios.

Diagram-4-Report-Rationalization.png

                                                                                          Diagram 4 - Report Rationalization Scenarios

Similarity across reports and level of overlap can be determined considering different parameters:

  • Database attribute overlap % - overlap in the database attributes used in the reports i.e. attributes that are used in the report query as well as the attributes that are displayed in the rendered report
  • Filters overlap % - overlap in the database attributes used in the report filters
  • Metrics overlap % - similarity in the metric names displayed in the report as well as in the metric definitions (for metrics computed at the report level)

Based on the nature and type of reports in a particular environment, these three parameters can be combined into a weighted score to indicate extent of report similarity and overlap e.g.

Report Correlation Index Score = 50% of Database attribute overlap + 30% of Filter overlap + 20% of Metric overlap

A threshold of 75% can be set and any correlation index score higher than the threshold score are good report rationalization candidates that can be further analyzed.

This methodology provides a structured and automated approach for conducting technical assessment of the existing reports. When dealing with a situation where we have a very large number of reports to be analyzed, this methodology enables us to quickly narrow down the focus on the cross section of reports that need to be analyzed further to confirm their rationalization disposition. This considerably limits the level of manually analysis effort that is required to complete the technical assessment. At the end of the technical assessment exercise, we have a good view of the set of reports that can be rationalized. The output of the technical assessment becomes a key input into the business assessment exercise. Since there is already a set of reports that have been confirmed for rationalization based on the technical assessment, these reports do not need to be included in the business assessment. The business assessment can be focused on other reports where report business intent, functional usage and grouping need to be confirmed with business stakeholders. This helps focus the business engagement on important areas that need business input and optimizes the time required from business stakeholders as part of the report rationalization analysis.

Implementation Details

We recommend an iterative 3-phased approach for implementing the report rationalization and migration initiative with an end objective to modernize and transform into an insights driven organization. The report rationalization and migration phases can be managed iteratively by reviewing the different considerations and assessing the different approaches to determine the best strategy that suits the specific situation.

Once the rationalization and migration phases have been completed and we have a streamlined reporting environment with reports that deliver maximum value to the business enabled by an optimal technology stack, the focus needs to shift to modernizing the reporting ecosystem with a focus towards transforming into an insights driven organization. At this stage, it is important to determine the specific newer capabilities that need to be enabled to deliver additional value to the business. While there are many options to consider, alignment across the Business and IT teams is crucial to define a roadmap of prioritized capabilities.

Diagram-5-Implementation

                                                                                   Diagram 5 – Implementation Approach

Outcomes and Benefits

Report rationalization, migration, and modernization initiatives offer many benefits:

  • Improving decision-making abilities – streamlining reports, eliminating redundancies, standardizing reports, promoting reuse, and aligning reports to specific business insights improve the quality of decision-making
  • Amplify business user experience – reports that are better aligned to various business user personas, provide more engaging visualization and consistent metrics and the KPIs improve trust, adoption, and overall user experience
  • Enhance processes and standards – such initiatives provide an opportunity to revisit and improve report related standards and delivery processes
  • Establish the foundation for a future-ready solution – a modernized NextGen reporting solution enables data and information to be further capitalized amplifying its value to the organization
  • Institute stronger consumption governance – instituting clear ownership around data, metrics, and reports enable an understanding of what, how, and who uses the information for decision-making. This allows data to be democratized while managing control and adhering to regulations.
  • Reduce total cost of ownership (TCO) – reduction in the number of reports, rationalization of BI tools, improved processes, use of accelerators, etc. all help in reducing the TCO

Coforge Value Proposition

Coforge has deep experience across many different BI tools and has worked with multiple clients across industries partnering with them on their BI and Reporting initiatives. We provide end-to-end BI services from BI strategy and roadmap definition, BICOE setup and operationalization, BI tool and report rationalization, BI development and support. Coforge has frameworks, methodologies, accelerators and jumpstart solutions that can be leveraged to improve quality, reduce risk and improve time to market for client engagements.

Conclusion

While the initiative to streamline and rationalize an environment with huge number of different types of reports may look daunting to begin with, embracing a holistic strategy and a structured framework for rationalizing reports and leveraging accelerators that can automate some of the effort intensive tasks can go a long way in ensuring success and delivering timely benefits. It is important to keep the end objective in mind of transforming into an insights driven organization as the existing reporting environment and BI tools are rationalized. This helps establish a solid foundation for the transformation that is needed to move towards a data native digital native organization.

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