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Agile teams have been working on their Product Backlog quality for quite some time. The best guidelines for splitting User Stories have been around for more than ten years:

While there is much experience on the team level, management who usually owns the top of the backlog has some work to do. I do think it is time to start splitting backlogs into small deliveries smaller items at all levels. It is not much different on whichever level you work on. We all like to have high throughput and fast A uniform handling of the backlog will create higher throughput and faster feedback.

I have found the guidelines for splitting User Stories useful also when splitting large business or regulatory initiatives. In this article, I have adapted the well-known patterns to give inspiration for the splitting of Epics. On this level, avoid user experience, instead, aim for organizational capability or business functionality. I choose to use the word Epic since it seems to be the most popular name for high-level backlog items. An Epic is best described as a business initiative

How Small?

Some sources, even Scaled Agile inc, refer to Epics as “large initiatives.” But think about the main idea to manage flow by optimizing batch sizes. Are Epics really an exception that cannot be small if needed? Of course not! The same logic is valid for all backlog items, regardless of who has ownership of them.

Every type of business has different demands, but lead-time should not be longer than your competitor's. I think most businesses want to be faster than 6 months, which is a long time to get feedback from customers and the organization. On the short side, make it as fast as possible. A two-week Epic would be really nice.

Which Pattern to Use

You’ll often find that you can split a story an Epic using several of the patterns. Which split should you choose? I use two rules of thumb:

Choose the split that lets you deprioritize or throw away a story. The 80/20 principle says that most of the value of a user story comes from a small functionality share. When one split reveals low-value functionality and another doesn’t, it suggests that the latter split hides waste inside each small story. Go with the split that lets you throw away the low-value stuff.
Choose the split that gets you more equally sized small stories. The split that turns an 8 point story into four 2 point stories is more useful than producing a 5 and a 3. It gives the Product Owner more freedom to prioritize parts of the functionality separately.

Perhaps the meta pattern 12. Always split by habitDo not aim for the perfect choice and do not regard these patterns as rules. Sometimes you can use a combination of patterns and sometimes you find new patterns. Start with something, get going, and learn.

On this level, avoid user experience, instead, aim for organizational capability or business functionality. Design details and solutions will have to come later when the Epics are broken down and getting implemented.

Commonly, regulations become large initiatives in organizationsEpics. These initiatives are “mandatory” and have a strict deadline. The regulations are thoroughly specified and can easily become big-bang implementations. I think you recognize the nature of such an initiative. I have chosen a well-known regulation called the General Data Protection Regulation (GDPR) as an example in the following breakdownsplitting patterns.

1. Workflow Steps

Identify steps or sub-processes that will occur in sequence within your organization, specified in or influenced by new requirements, and then define these steps as separate incremental initiatives.

Our entire business must be GDPR-compliant from 25 May 2018

  • Information to individuals about your collection, purpose, and usage of personal data

  • Collecting and storing of personal information

  • Governance of personal data

  • Manage requests from individuals about personal data

  • Removal of personal data

Tip: Do not make the mistake of using the sequence in your development process—first, analysis, then design, and so on. Only look at your operational value stream!

2. Rule Variations

Since a large initiative, especially regulatory, have plenty of rules, this pattern is obvious. Some rules are more complex or extensive and serve as a single initiative. Other more straightforward rules may be grouped in clusters.

Seek to find high-level rules you can understand from a business perspective. In this case, break down the initiative into several initiatives to implement one at a time.

Our entire business must be GDPR-compliant from 25 May 2018

  • Processing data that identify individuals

  • Processing data about interactions with our business

  • Processing data that reveals individual attributes

  • Processing data which reveals the relation between individuals

  • Processing that does not require the identification of individuals

Tip: Take the opportunity to assign business value to each rule, requirement, or type of information. Down prioritizing or even dismiss

3. Major Effort

Sometimes an initiative can be split into several parts where most of the effort is hiding in the first one.

For example, awareness of where personal data is stored and the legal obligations are developed to support the first initiative. The implementation of further initiatives should have much less uncertainty.

Our entire business must be GDPR-compliant from 25 May 2018

  • Maintain a record of processing activities (article 30 register)

  • Communication to individuals

  • Cooperation with authorities

  • Processing of personal data in various systems

Tip: When talking about the effort, it is easy to break out technical infrastructure as one or several enablers. Enablers may be delivered first, as a kind platform, but are not used and evaluated until real usage in the operational value stream. Avoid enablers as far as possible. Instead, split Epics into something which can be used in your business.

4. Simple/Complex

When your organization discusses an initiative, and the solution seems to be getting larger and larger, and the path to an agreement is unclear, then stop and ask, “what’s the simplest thing that our business could benefit from in this area?” Capture that simple version as a separate initiative, and then break out other variations into different initiatives.

Our entire business must be GDPR-compliant from 25 May 2018

  • GDPR-compliance in the Value Stream “new emerging business.”

  • GDPR-compliance in internal HR-systems

  • GDPR-compliance in Customer Relationship Systems

Tip: Modularization is the best thinking pattern to reduce complexity. Components with purpose and a defined interface are usually clean-cut that easily get acceptance.

5. Variations in Data

Data variations and data sources are other factors of scope and complexity. Consider adding initiatives just-in-time after building the most straightforward version—an example of where different purposes and sources have been used here.

Our entire business must be GDPR-compliant from 25 May 2018

  • Personal data intended for obligations to employees

  • Personal data intended for marketing and sales

  • Personal data intended to improve product quality

  • Personal data acquired from third parties.

Tip: Not all data may need to be real or updated in real-time. Early versions can thus use mocked, manually or seldom updated information.

6. Data Entry Methods

Sometimes complexity is in the communication rather than the business process. In that case, split the initiative to build it with the basic communication first and then richer alternatives to collect data.

Our entire business must be GDPR-compliant from 25 May 2018

  • Aquire personal data when signing agreements

  • Aquire personal data through voice calls

  • Aquire personal data through messaging such as email

  • Aquire personal data through surveys or signup for newsletters

  • Aquire personal data through product and service usage

Tip: Do not forget to involve the UX-people in the process of managing the backlog.

7. Defer System Qualities

Sometimes, the initial implementation isn’t all that hard, and the major part of the effort is making it fast
– or reliable – or more precise – or more scalable. However, the team can learn a lot from the basic
implementation, and it should have some value to a user who wouldn’t otherwise be able to do it all.

In this case, break the initiative into successive “ilities.”

Our entire business must be GDPR-compliant from 25 May 2018

  • Store personal data in plain text with manual monitoring

  • Pseudonymisation and encryption of personal data

  • Automatic monitoring and processing

Tip: Always work on the evolving Definition of Done. The best is to have an ongoing discussion of quality, responsibilities, and when a solution is finally delivered.

8. Business Operations

Words like manage or control are a giveaway that the initiative covers multiple operations, offering a natural way to split the initiative.

Our entire business must be GDPR-compliant from 25 May 2018

  • Resource management

  • Product development

  • Marketing, sales, and delivery of product or service

  • Legal

  • Economy

Tip: Think only about running the current business. When involving future business, it is easy to wind up into a meta-discussion and increase the delivery complexity. For example, operations of Product Development involves data of the employees, suppliers, or partners.

9. Business Use Case Scenarios

If use cases have been developed to represent complex user-to-system or system-to-system interaction, the initiative can often be split into individual use cases.

Our entire business must be GDPR-compliant from 25 May 2018

  • Order product or service

  • Receive product or service

  • Payment

  • Get support

  • Terminate business relation

Tip: Do not Use Cases as a Carved in Stone approved requirement specification. When used as a creative tool in workshops, Uses Cases is fast and straightforward to create a mutual understanding.

10. Break Out a Minimum Viable Product (MVP)

In many cases, the market is uncertain, and it is hard to understand all parameters from a business perspective. Our instinct is to also deal with uncertainties regarding the ability to deliver the solution. On this level, however, we should only focus on the business perspective and assume that, in any case, we will be able to deliver a feasible solution. If an initiative gets prioritized, the teams will later have plenty of opportunities to deal with technical uncertainty through spikes and other measures.

When doing an MVP, start from an assumption and then develop a hypothesis validated through an experiment. Rather than just an experiment, an MVP and the Build-Measure-Learn concept is a scientific approach to understand the business priorities. To exemplify, the reader will find some alternative assumptions to the right. To compare with the usual and introvert assumption to the left.

If we are not GDPR-compliant by 25 May 2018, high penalties may jeopardize our business.

  • Customers will love when their personal data is secure, which in turn will lead to increased business.

  • By an early announcement of secure and ethical handling of personal data, the corporate image will be stronger.

  • By structured and secure handling of personal data, we will lower costs for development and customer support.

Tip: The essence of experiments is to provide results quickly. It is a warning sign when it takes several weeks to get the result out of an MVP. Remember that “M” in MVP stands for “Minimum.” When coding is involved, there is a risk the meaning of “M” will change to “Maximum.”

11. Non-functional requirements

When there are plenty of legacy systems in an organization, a more radical pattern may be the most feasible. Simple, scrap the whole initiative or exclude some systems, departments, or other partitions. Maybe some systems are already in the plan for decommissioning. Is it worthwhile to invest in upgrading old systems or instead live the gap or advance retirement?

Remember that a pattern is not an exact rule for splitting the backlog but aid in finding alternative ways of thinking. You may end up breaking the backlog in a different way than you thought when starting working on a pattern, and that is OK.

In many cases, a combination of patterns is to recommend. For example,… To combine several splitting patterns is a pattern in itself.

Do not allocate people to do detailed initial studies. Dive into the summaries, often provided by authorities or even found on the internet, instead of reading exact specifications or regulations. Instead, discuss the impact on your business and then split your Epics and get started. Delivering is the action, and learning is the reward, whether you fail or not. Just make sure to fail safely!

To make the splitting work, you need to start delivering definitive solutions early and not wait until just before the deadline. Prioritize your learning. It is the main factor to enable delivery in time with the right quality.

12. Always split by habit

The most difficult is to avoid saying, “We know we must implement these regulatory requirements, so why to bother to split it into separate Epics. Let’s decide and let the organization take care of it.” It isn't easy because it is intuitive and normal to look at a large Epic as a monolith, which is best kept and will not create any benefits until fully accomplished.

If