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Even if Agile has been widely implemented on the team level, many organizations retain their habit of having experts making thorough analysis and planning. This practice lulls people into a false sense of security as they believe estimates are accurate. The plan is presented to the management, who gives the appropriate go-ahead on large initiatives. The Agile teams are then expected to split the backlog and deliver the solution in small valuable increments.

The rigid pre-planning is a struggle for the Agile teams who are confronted by fixed solutions and promised deadlines. The teams need to work on several initiatives simultaneously, while the experts are doing more analysis and planning to keep the work queue prepared. These and many other organizational obstacles destroy the creative power in a team setup.

I think most people understand that the It is normal that organizations want more outcomes from their Agile transformation. On the positive side, problems are now more apparent, and there are Agile teams prepared to take responsibility. But the queue of urgent matters is still long, and the quality is not getting better.

Even if we can see that pre-planning of large initiatives is not an ideal way of working, and not much different from what we used to do. The queues are still long, and the quality is not getting better. The positive side is that the problem is now more apparent, and we have teams prepared to take responsibility, it is indeed hard to change. Most people I speak with ask: “How can we then know what to do if we don’t investigate first?”.

The major challenge is to let go of too rigid planning. To accept the uncertainty and instead implement the Lean-Agile mindset also when preparing and prioritizing large initiatives. Difficult? Of course , it isn't easy, but without ambition and courage, it will never happenvery difficult, but many organizations need to increase quality and throughput and it is time to grasp the entire product backlog. It is time to get the real benefits of your Agile transformation.

Try to resist the following thinking:

  • We better get everything done while we are at it.

  • We cannot get all of the business value before we have done the entire thing.

  • Before we start, we need to make sure we understand all of it.

  • We will avoid surprises if experts investigate everything before we start.

  • Management is responsible and needs a well-prepared decision basis for large investments.

Instead, promote the following thinking:

  • The faster we can deliver, the faster we get valuable learning.

  • Big things are more complex than small, and complexity is evil.

  • It hurts less when failing with something small.

  • Decisions about small initiatives are more comfortable to delegate to people closer to the business.

  • It is much more productive to have a flow of small things than working in parallel on large items.

  • With small and frequent deliveries, people get more engaged, and their creative contribution will positively impact.

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.

To get going, guiding patterns can be beneficial. Many teams use “ten common patterns to split a user story,” included in the white paper “A User initiative Primer.” These patterns can inspire at any level of a product backlog breakdown, and the adoption in this article shows how the splitting patterns can be applied at the first Epic creation moment. It is best to have the white paper in front of you and compare the patterns to split a User Story.

Commonly, regulations become large initiatives in organizations. These initiatives are “mandatory” and have a strict deadline. The regulations are thoroughly specified and can easily be thought of as a big bang implementation. 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 breakdown.

I have found the following patterns useful when splitting large business or regulatory initiatives. The examples mentioned below are one way to think; there may be another hundred. Only you know the prerequisite of your organization and can find the optimal split. Avoid user experience and, instead, aim for organizational capability or business functionality.

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. Splitting is habitual

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