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Problem Data Quality Issues dashboard

The Problem Data Quality Issues dashboard enables you to understand your overall data quality, from a data completeness perspective. Using this dashboard, you will be able to identify areas in which there is no proper data maintenance, details about current data completeness situation, data completeness trends (whether it is improving or reducing over a period of time), areas in which it is lagging and by what percentages, list of Problems that need to be completed from a data quality perspective, current stage of Problem life-cycle, data quality performance, and so on.

With this information, it is possible to analyze and reduce data quality issues. This will also potentially lead to overall improvement in resolution parameters, adds value for Knowledge Bases and helps in re-usability of Problems for reference perspective.

The Problem Data Quality Issues dashboard can be of great value to answer some of the following business questions:

What is the overall data quality from completeness perspective of Problems and how does that fare at different status of Problem life cycle. What are the Problems that contribute to the data quality in each status?
What is the average DQ incompleteness at Problem's level and across Problems? Sort them based on the maximum DQ incompleteness so that those can be looked at closely
Which attributes have a higher rank of DQ incompleteness. Sort them so that there could be a organization level plan for these attributes and teams can be trained for those

There are two chapters in this dashboard that can be used for analysis. The first chapter is the Problem Data Quality dashboard which gives you numeral statistics about Problem data quality. You have the option to view data sorted on basis of department or leadership.

The second chapter is the Problem Data Quality Details using which you can deep dive into the Problem Data Quality trends, based on calendar month.

Problem Data Quality Issues

The Problem Data Quality Issues chapter has two pages:

Problem Data Quality Issues by Department
Problem Data Quality Issues by Leader

The Problem Data Quality Issues by Department page provides insights into some of the KPIs, based on the department selected. A heat map is displayed to indicate data quality positioning of each department. On selecting the required department, KPI values are refreshed (displayed to the right of the page). The KPIs available in this page are:

Weighted Avg. Poor Data Quality across Status: Displays the overall Problem Completeness Data Quality with weighted averages by Problem status
% of Fields with Poor DQ across status: Displays in percentage, the average of Factors with data quality issues as compared to all the factors reviewed for Data Quality
% of New Problems with Poor DQ: Displays the percentage of Problems with Data Quality completeness issues as compared to Problems that are in the 'New' state
% of Poor DQ Problems are Reopened: Displays the percentage of reopened Problems with Data Quality issues as compared to all reopened Problems
% of Poor DQ Problem : Displays the Ratio of Problem that have poor data quality as compared to total Problem for a specific period of time.
% of Poor DQ Problems have reassignments: Displays the percentage of reassigned Problems with Data Quality issues as compared to all Problems that have been reassigned
% of Closed Problems with Poor DQ: Displays the percentage of Problems with Data Quality completeness issues as compared to Problems that are in the 'Closed' state
% of Poor DQ Problems delivered past due date: Displays the ratio of delay in delivery of Problems where Problems have Completeness Data Quality issues to delivery age of Non Data Quality issue Problems

The Problem Data Quality Issues by Leader dashboard displays the same KPIs, with the only difference being that the KPIs are sorted on the basis of leadership. A bubble graph is displayed to indicate the data quality positioning based on leadership. KPI values are refreshed upon selection of bubble.

Problem Data Quality Issue Details

The Problem Data Quality Issue Details chapter has three pages:

New Problems
Closed Problems

The Problem Data Quality Issue Details dashboard basically lets you deep dive into the Problem data quality trend, on the basis of a given calendar month.

Data displayed on every page is based on the status of Problem with data completeness issues. However, the KPIs displayed for each remains the same. The first page displays Problems in 'New' or 'Open' state and the last page displays Problems in 'Closed' state.

A graph to indicate the Creation DQ ratio for a given month is displayed in the first panel. If you select a month, data in the subsequent panels are refreshed. For example, on selecting Dec 2019, factors such as Affected CI, Assignee, Assignment group, Due Date, Resolution Code, and so on, that affect data quality completeness by Problem status is displayed for that month. Similarly, the panels to the right indicating factors such as Select the value display criteria, and so on are refreshed based on the factor you select in the 'Factors Completeness Data Quality' panel.

Similarly, the tabular data displayed in the 'What Problems have poor data quality?' and 'What are the field values for the selected Problem?' panels are refreshed based on the selection made in the 'What are the values for the selected field?' panel.

The KPIs available in this page are:

Total Problems with Data Quality Issues: Displays the total number of Problems that have data completeness issues with respect to current status
% of Fields with Poor DQ across status: Displays in percentage, the average of Factors with data quality issues as compared to all the factors reviewed for Data Quality
Select the value display criteria: Displays the percentage of DQ Problems across factors as compared to the total Problems
DQ Problems Across Factors: If the value of this metric is 1, it means the Problem has a data completeness issue in at least one of the factors

Metrics Used

Metric Name	Descriptions
Total Problems with Data Quality Issues	Count of Problems with Data Quality completeness issues This is a level based metric calculated only for Department, Leader, Month, or State (standardized state)
Weighted Avg. Poor Data Quality across Status	Overall Problem Completeness Data Quality with weighted averages by Incident status
% of Poor DQ Problems have reassignments	Percentage of reassigned Problems with Data quality issues as compared to all reassigned Problems
% of Poor DQ Problems are Reopened	Percentage of reopened Problems with Data Quality issues as compared to all Problems
% of Poor DQ Problems delivered past due date	Ratio of delay in delivery of Problems with completeness data quality issues to delivery age of non data quality issue Problems
% of New Problems with Poor DQ	Ratio of Problems that are in the New state and have data quality issues
% of Poor DQ Problem	Displays the Ratio of Problem that have poor data quality as compared to total Problem for a specific period of time.
% of Closed Problems with Poor DQ	Ratio of Problems that are in the Closed state and have data quality issues
% of Fields with Poor DQ across status	Average of total factors with data quality issues as compared to total number of factors
DQ Problems Across Factors	If the value of this metric is 1, it means that the Problem has a data quality issue in at least one of the factors
Rate of Problem DQ Issues Across Fields	Total Problems with data quality across factors by total number of Problems
New Problems	Count of Problems in the New state
Closed Problems	Count of Problems in the Closed state