Introduction

I have been in the Data & Analytics space for over 20 years. Without exception, I have continually seen that the most successful D&A projects are also the ones that have a Customer focused Agile Data Delivery mechanism in place.ย  It is truly amazing to see these projects consistently churn out new BI content while maintaining business user satisfaction at the highest levels.ย 

The following are my personal observations of how the most successful projects operate…

Agile Data Delivery

Data & Analytics (D&A) is a critical function for todayโ€™s modern โ€œdata drivenโ€ enterprise. Everyone wants happy Business Consumers, so it is quite common to focus a disproportionate amount of time and effort on their more visible front-end reporting & DataViz needs. This front-end focus can result in spending too little time implementing the vital rock-solid Data Delivery back-end. An unbalanced Data Delivery ecosystem like this can contribute to consumer frustration due to a lack of timely and useful data, trust issues with the data, and a general decrease in user adoption. It can quickly become the โ€œbeginning of the endโ€ for a D&A project.

โ€œAgile Data Delivery can be magical, if done correctlyโ€

Scroll through the following flash cards – These are just a few of the key components to Agile Data Delivery. There are many more. However, if you get these in place, I have seen that a project will be off to a great start with its journey towards Agile Data Delivery and the benefits that will fall in place down the road.

1 - Yes to Agile

 

To โ€œdeliver data with agilityโ€, one needs to first forget about the traditional waterfall delivery method. It just does not work in todayโ€™s modern data-driven enterprise. Consumers can no longer wait months or years for data to be populated into the Data Warehouse / Data Lake. The modern Consumer needs data โ€œnowโ€ to make timely data driven decisions.

2 - Data Delivery Team

 

Get the right mix of folks in place. Even if this is an IT driven Data project, you will need a mix of IT and Business personnel.ย In addition to IT, Data Architects, Data Integration and Business Intelligence developers, you need to have your key Business stake holders at the table.

3 - Data Story Backlog

 

With your well-rounded team in place, meet at least once a week to discuss your Data Stories. What data does the business need to have access to? What is the priority for each Data Story? Do we already have this data? How does this data fall in line with Enterprise goals? The aim here is to identify as many Data Stories for our Agile Backlog (stuff we need to do).ย 

Part of the process will also be to identify the individual Data Stories that will be worked on during the next Sprint. Having both IT and the Business involved in these discussions will ensure that everyone knows what the deliverables will be for the next sprint. And more importantly, there will be no surprises when delivery is completed.

4 - Sprint

 

The project manager will meet with all the IT teams and coordinate the delivery of the sprintโ€™s Data Story. If this is new data, the Data Integration people will source the data and build ETL/ELT logic around the process. Business Intelligence developers will take this new data and build out the reporting deliverables as indicated by the Data Story โ€œcardโ€.

 

Since all these tasks can take quite a while, a single large โ€œEpicโ€ Data Story may be broken up into multiple stories โ€“ one for the Data Integration piece and one for the BI Reporting piece. These โ€œEpic Storiesโ€ can then be spread over multiple sprints depending on the complexity. But that is OK, as both IT and the Business will already know the story delivery cadence, so expectations will already have been set.

5 - Delivery

 

To speed up delivery of a Data Story, ensure that you slice and dice your deliverables into workable chunks of work. Individual Stories / deliverables should fit in a single sprint (two-week sprints are relatively common for D&A projects).

 

Delivering quickly will allow the Business to see tangible progress sooner. Based on what the Business sees, the Data Story can be marked as completed as expected, or it will result in some rework, which will be prioritized and slotted into an upcoming sprint.

 

The magic of โ€œDelivering Fastโ€ is that you will also โ€œFail Fasterโ€. This isnโ€™t a bad thing โ€“ the sooner the Business sees a problem, the sooner it can be adjusted. With the old Waterfall delivery method, the Business might not see issues for months, resulting in a lot more rework and back tracking.

6 - Deployment

 

Once the Data Story has been delivered and approved by the Data Delivery Business liaisons, it is time to involve the greater Business community. This is a vital step that will really help with overall adoption.

 

The Business liaison on the Data Delivery team will also be a key person to help with onboarding, education and soliciting feedback from the community. It is critical that the community be educated as to what the new functionality can and cannot be used for. To help with this education, demos given by the Business Liaison and the BI developers are also vital.

 

Weekly โ€œOffice Hoursโ€ can also be activated so that Business Users can โ€œdrop inโ€ and ask any question and see focused demos with the Data subject matter experts.

7 - Monitoring

 

Critical to User Adoption is constantly monitoring and usage auditing of the new Data feature. Are Consumers using the new feature? How often do they access the new feature? These are just some of the metrics which are vital to understand if our agile project has been successful or not.

 

If a usage issue is identified, the Data Delivery team needs to reach out to the Business team and curate a proactive plan to tackle the issue. This could include re-running the โ€œOnboarding Sessionsโ€, running some โ€œLunch and Learnsโ€, or just dropping by the userโ€™s desk and โ€œChecking Inโ€ to see how things are going…

 

Being proactive rather than reactive to user adoption issues can make all the difference for the success of a Data Delivery project.

8 - Repeat

 

The final step is to return to your Data Story backlog. Reprioritize or adjust your stories, if necessary. Then, kick off the next Data Sprint.

 

After a few successfully delivered sprints, Business users will feel more confident about all the data stories being delivered. They will feel more empowered because they have a say in โ€œWhatโ€ and โ€œWhenโ€ Data Stories get delivered.

Hope you find these thoughts useful…