How to Ensure Data Reliability in High-Level Reporting [PPM]

High-level reporting is central to Project Portfolio Management. The ride data takes from a work team to the senior level can either be bumpy or incredibly smooth. What influences the quality of high-level PPM reports? How to ensure the accuracy of data that fuels the portfolio-level reports?

What distorts business data?

Experian, in its Global data management research, claims that the biggest contributors to a lack of data accuracy were human error (50%) and too many data sources (39%).

—One of the biggest challenges in leveraging data to its full potential is a lack of trust. (…) Lack of trust in data paralyses organisations, preventing them from making decisions and embarking on strategic projects. Distrust can cast doubt on an entire project, even when only a small segment of the data is inaccurate. This results in two scenarios. Either businesses bury their heads in the sand and execute projects using inaccurate information, or a lack of trusted data acts as an excuse for decisions not to be made and keeps businesses from innovating. Either way, the outcome is negative?– said Steve Philpotts of Experian.

Digging deeper, Experian lists challenges all data management approaches have:?Eighty-nine percent of businesses report that they struggle with managing data. These struggles include delays in insight (42%) and a lack of trust in underlying data (40%).1

While Experian is a credit reporting company, research by datapine, a data visualization and business intelligence software company, names five pillars of Data Quality Management. The first pillar is ‘The people’.

Data reliability in PPM reporting

PPM is no different. Project Portfolio Management reporting depends heavily on data supplied by work teams. Here at SoftwarePlant, we see the following chain of events affecting the reliability of high-level data at our clients:

1. Work teams prefer popular work management software, such as Jira or Trello, while the PMO and senior executives typically use specialized PPM tools.
2. To keep the senior executives informed, project/product managers copy and paste data between different pieces of software.
3. A human error, or equally often somebody’s hidden agenda (rounding data up or down to gloss over certain indicators), might affect the reliability and validity of data the PPM tool gets.
4. PMO is updated on the progress of individual projects and products with a delay of one week or so.
5. Senior managers get to know the progress of the whole portfolio a week late.
6. One can question the reliability of the portfolio-level reports.
7. Distrust occurs.
8. The Single Source of Truth concept fails. The bird’s-eye view or big picture of an organization is of poor quality and not live.

Conclusion

Figure 4. Trello updates high-level Overview of BigPicture.

The human factor affects the quality of the PPM reports most.

Only the tools that teams truly love, such as Trello, can output quality data. If tasks in that Trello had incorrect To do / In progress / Done statuses, how would the teams navigate?

Umbrella PPM apps accept connections from those third-party tools. BigPicture uses live, dependable data, arriving from Jira and Trello, for high-level progress reports.

Umbrella apps should also provide a standard PM toolset, evident in the menu.

BigPicture, an umbrella app

Is there a viable solution to the PPM data reliability challenge? We think there is, and that is how we’ve designed?BigPicture, an umbrella PPM app for Jira and Atlassian ecosystem.

Learn more on the?BigPicture?blog.