Become an Enterprise Architect of Tomorrow: Part 2

Posted by Lesa Moné on 04 December 2017

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In the previous installment of this series, we detailed a few top traits that Enterprise Architects of the future should have to bring measurable value to their enterprises. This last installment  includes more traits, and actionable tips on how to develop and implement said traits. 

KEY TRAITS OF TOMORROW’S ENTERPRISE ARCHITECT

Agile mindset

Agility has become a key characteristic of a top performing Enterprise Architect (EA) of tomorrow. An important EA goal is to implement enterprise-wide agile methodologies to speed up software deployment timelines. High performing organizations deploy code to production 46 times more frequently than their low-performing peers. Innovative companies like Etsy report deploying 80 times per day, and companies like Amazon engineers deploy code every 11.7 seconds, on average, and Netflix report deploying thousands of times per day. 

“High performing enterprises reported their lead time required to deploy changes into production (i.e., go from code committed to code deployed and running successfully in production) was less than one hour, whereas low performers required lead times between one week and one month. So the high performers had 440 times faster change lead times than low performers. For our calculations, we used lead times of 60 minutes for high performers, and 26,940 minutes for low performers (the mean of 10,080 minutes per week and 43,800 minutes per month)”. - 2017 State of DevOps Report

Once shifted over from the “Ivory Tower” mindset to a project manager mindset, EAs can actively map out frameworks that foster high project deliverable rates, generate quick results and produce reliable critical business data while respecting all the important requirements like security, data privacy, and compliance.

One example of agile development that should be explored by EAs is scrum frameworks. Scrum is a widely adopted agile framework for completing complex projects. Scrum was originally formalized for software development projects, but it works well for any complex, innovative scope of work.

The scrum framework works as follows: the teams create a prioritized list called a product backlog. During spring planning, the team selects a small chunk from the list, a sprint backlog, and decides how to implement those pieces. The team, directed by the EA, has a certain amount of time - a sprint - to complete its work. Every day there is a daily scrum to assess its progress.

Along the way, the Scrum Master keeps the team focused on its goal. At the end of the sprint, the work should be potentially shippable - ready to deploy, send to the customer, or show to a stakeholder. The sprint ends with a sprint review and retrospective. The major difference between the scrum framework and traditional slow EA frameworks is that a sprint usually lasts from two to four weeks versus months or even years like EA processes in the past.

When producing quick plans and generating quick results, EAs can help teams accelerate time to market, increase productivity, and respond to changes in the stakeholders priorities. Scrum is a key framework tool to an agile EA. Scrum produces regular valuable output, allows you to realign your targets when necessary, change an objective at every review, and provides a short feedback loop. Even faster than the scrum system is the Kanban method which emphasizes on just-in-time delivery. Project deliverables can be produced in mere hours - a clear indicator of an agile team.

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Figure 1: The principles of scrum

Make data-driven decisions

“Data will become a strategic asset to the adaptive enterprise and analytics will enable the organization to distinguish the signals from the noise and focus on outcomes, resulting in business ROI.” - Björn Goerke

All decisions that EAs of tomorrow make must be based on data. Data-driven decisions help leadership make the right investments and ensure the organization is working on the most impactful tasks to improve competitive advantage.

High performing EAs are on top of up-to-date analytics, prove hypotheses with data, regularly A/B test the practicality of current systems, and make decisions only from admissible data. We live in the age of an overabundance of data - having direct access to a variety of expert tools that constantly generate a flood of information, the real task for EAs is to determine which data is useful, and to utilize said data in a meaningful way.

The web-based software Zendesk has revolutionized the customer service of many companies by streamlining communication formats, bundling all customer communications in one place, and providing up-to-date analytical tools. Without access to up-to-date data, customer support suffered from backlogged tickets, lost communications, neglected issues, slow response times, and disorganized files.

Zendesk’s intuitive dashboard provides clear visibility into customer interactions, and produces in-depth analytics using machine learning algorithms to enable your enterprise to better understand and predict customer satisfaction, measure performance, and uncover actionable insights.

Data from tools like Zendesk directly enables EAs to make data-driven decisions from detailed figures and analytics organized on a clearly illustrated dashboard. This valuable informational and organizational style can help facilitate improvements in customer service which in turn creates a culture of professionalism and develops measurable improvements in the business strategy.

Evangelistic

Whereas EAs of the past were seen as data collectors, creating far-flung models for various project teams, EAs of the future must see a benefit in constant application changes - and be able to convince teams to test out new processes.

Evangelistic EAs would pick one important topic that would greatly benefit the company whether it is microservices, DevOps, cloud migration etc., and research, zealously advocating the particular cause.

One hot topic for most industries is IoT. Technology research firm Gartner predicts that by 2022, IoT enabled service models could save a trillion dollars a year in maintenance and service costs. Forward thinking EA’s of tomorrow will take this information, research which IoT technologies would provide opportunities or threats to their organization, and provide a broad understanding of the business impacts of IoT technologies, based on the technologies’ characteristics, the information they expose and how they will be used. By thoroughly researching the technology, and the resulting ideation, evangelical EAs can provide internal teams and IT leaders with more than just a list of “cool” technology ideas.

HOW TO DEVELOP THESE FIVE TRAITS AS AN EA

Do not accept bad quality data.

Not all data is useful for business decisions. Real time relevant metrics are an EA’s best tool. Ask “Is this data still relevant?” before making any subsequent changes to the framework.

Be easily accessible.

Constantly check in with each team and know what changes they need before they need it. Schedule review meetings as often as needed.

Use an Enterprise Architect Management software.

Be sure to select software that offers state-of-the-art reports that are automatically adjusted in real time. Read about LeanIX’s software tool.

Constantly look for areas to improve.

Ask questions like, “Are these tools still relevant?” or “Is this system working?” or “How I can I make this framework run more smoothly?” on a consistent basis.

Attend industry conferences.

A great event to put on your calendar is EA Connect Day. 230+ EAs and IT leaders come from around Europe to share industry insights. Also, check our calendar for world-wide EA events

Listen closely to the needs of your team.

Teams that can decide which tools they use are better at continuous delivery. This is in contrast to teams that can use only those tools that are mandated by outside influences. Teams that can choose their own tools are able to make these choices based on how they work, and the tasks they need to perform. 

Constantly learn.

Enroll in relevant university tech courses to stay abreast of emerging industry standards and apply constructive knowledge to current projects.

Collaborate with the best.

Leverage the experiences of innovative vendors that bring demonstrable experience on new topics that you need to drive.

Try an agile method.

Apply scrum or Kanban to a current project that is taking too long to deploy. Do not ask upper management for permission. Get started on a product backlog and start delegating tasks today.

Get started today.

Pick one current project where you can apply these traits and make a measurable difference for your company. 

CONCLUSION

EAs with tunnel vision on long-term plans and conceptual processes are not valuable to their teams. EAs of the future architect the enterprise framework as a problem-solving tool to drive digital transformation. Strive to master all above mentioned traits - ability to execute, tech savvy, agile minded, make data driven decisions, and become evangelistic to make measurable impact on your enterprise.

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