3 Key Agile Principles to Drive Your Digital Transformation Journey to Success

3 Key Agile Principles to Drive Your Digital Transformation Journey to Success

Learn the strategies and steps to take to fully reap the benefits of digital transformation for your industrial operations.

Once a buzzword, digital transformation has now become a critical part of many industrial manufacturers’ strategies. Amid the COVID-19 pandemic and shifts in the market, the push to integrate digital technologies and data to improve overall output and maximize workforce productivity have been magnified.

By taking full advantage of the power of transformative technologies, manufacturers can move into greater resilience, adaptability, and proactive innovation as they scale, stepping into the realm of the Connected Enterprise®.

Yet, it can be challenging to begin.

This piece aims to help organizations make the most of their technology investment and realize rapid value while maintaining three solid agile principles throughout their digital transformation journey.

Phase 1: Strategize - Focus on digital transformation imperatives

Transformative technologies present exciting possibilities, so the desire to level up quickly is understandable. That said, it is easy to get focused on technology parts and pieces and miss the broader elements critical to success.

Addressing the following digital imperatives lays the foundation for a comprehensive, iterative strategy that continually drives rapid value from technology investments. 

Define organizational values and business strategy

You cannot achieve or measure what you do not define. Developing clear business goals, objectives, and challenges set the stage for an effective digital transformation blueprint, clear architecture, and viable roadmap for future phases. Before you do anything else:

• Specify the key purpose or “North Star” and define business goals.

• Outline challenges and roadblocks.

• Identify and prioritize the right use cases to achieve your goals.

• Identify personas (the roles/people who will benefit or be impacted) and relevant KPIs.

These four areas can link every element of design and deployment back to data, personas, and user stories – paving the way for ongoing iteration that easily scales. Clarity here streamlines every stage of the digital transformation journey.

Prioritize accelerated time to value use cases

By proving the value of digital transformation efforts quickly, manufacturers can more easily gain the confidence of key stakeholders and keep them engaged throughout the process. More importantly, such use cases can demonstrate the viability and scalability of specific features and processes across the enterprise. Combined with the early integration of analytics, use cases yield solid data and proof points.

• Prioritize uses cases by how quickly they are realized to value: Choose a narrow focus that will easily show viability and scalability.
• Endeavor to demonstrate substantial KPI improvement: This helps secure further investment, reduces risk, and builds toward greater long-term success.
• Map out the Now, Next, and Later for each use case: Assess individual use cases in current state and future state, and always link the cases back to the people who will use and benefit from the solution and data.

Tap on the expertise of a proven digital transformation implementation partner

A solid digital transformation partner should have implementation expertise in their domain, the ability to showcase proven results, and the means to help effectively measure rates of adoption and productivity changes across the value chain.

Look for a trusted partner that has a portfolio of successfully implemented projects, with case studies and proof points that demonstrate a comprehensive understanding of digital transformation imperatives for the industrial manufacturing industry.

In addition, this partner should possess a robust ecosystem of technologies, models, and collateral, including a rich application library.

Lastly, the company should have a comprehensive methodology that is designed to support the ongoing cyclical nature of digital transformation. This methodology should build on a combined analytics-technology foundation, focus on human-centric design, and account for the complexities of change management to adapt to new systems and processes in an agile manner.

Phase 2: Execute - Implement and deliver your solution

The steps to implement digital transformation vary based on each organization’s specific business objectives. The aim is to work within a methodology that is flexible and iterative that aligns with the implementation goals.

Keep in mind that effective digital transformation impacts every aspect of a business, including operations, processes, and people on levels both overt and subtle. Addressing the nuances of business and operations helps with implementing the right transformative technologies in the right way, to best serve the business’ objectives and its people.

• Empower people via human-centered design

Effective digital transformation focuses on empowering employees with new technologies that help them work more easily and efficiently to further drive business value. As mentioned above, it is important to identify the personas critical to the digital transformation journey in the Strategy phase. The next step is to focus on human-centered design.

The Execute-Implement phase calls for diving deeper into persona roles and responsibilities. Accurate persona information helps validate the effectiveness of new solutions and can ease adoption and adaptation. Successful digital transformation efforts should always come back to personas to ground innovation cycles, and advance human-centric design and human-technology collaboration as the business scales.

Facilitate persona interviews to understand the roles, responsibilities, and activities of every member of the workforce. Take note of employee challenges and pain points, and their aspirations for job success. Manufacturers can then use this information to assess the organization’s need for new skill sets. Examples of personas include product owner, solution user, user experience designer, QA tester, technical lead, and so on.

The next step is to build persona-centered clickable prototypes, analytic data dependency maps, and representational examples. These help with learning and validation prior to doing actual development, which is more costly to change later. The process demonstrates realistic viability for the workforce, including ease of use, if the targets are right, and scalability across the enterprise.

Following this stage, validate the solution with users and test business cases. Lead interactive and iterative sessions to fine-tune design and create tangible, visual, experience-driven mockups specific to the personas. Building persona experiences of use case applications in a mock-up environment can yield valuable data and point to critical dependencies. It can also help to drive stakeholder and workforce consensus for eventually adopting the new solutions.

• Utilize data and analytics to set the foundation for change

According to Gartner, “Data and analytics are the key accelerant of an organization’s digitization and transformation efforts. Yet today, fewer than 50% of documented corporate strategies mention data and analytics as fundamental components for delivering enterprise value.”

The right data foundation supports target blueprint architectures and unlocks critical enterprise-level insights that empower a company’s vision for scale. The big question is: How do you get the most value from your data?

Prototypes, analytic data dependency maps, and other representational examples can deliver invaluable data. Other key sources include enterprise resource planning (ERP), customer relationship management (CRM) and sensor data. If need demands, consider creating an operational historian or generating required data such as downtime data.

The importance of utilizing the right data and analytics from the onset cannot be overemphasized.

For one, data helps to create and validate a clear, target digital transformation blueprint. By identifying, connecting, and integrating key data sources, companies can gain both comprehensive insight and oversight of your business and operations, yielding invaluable indicators on areas of concern and opportunity.

Secondly, data readiness, quality, accuracy, and readability across enterprise sources and systems empowers the roadmap. Building relevant OT data context will help an organization generate higher value actionable insights. Incorporating OT context at the edge and building common information models between IT/OT systems can significantly reduce data preparation efforts by data scientists and IT analysts. Dashboards with the right data foundation help to further connect the dots across industrial data silos.

• Deliver solution and set for scale

Success depends on a strong initial delivery that aligns with the overall purpose. Manufacturers must measure their progress and the scalability of new solutions by consistently aligning with their objectives and key results.

Identifying business cases and results expectations upfront gets the organization focused on the important elements of the project. It can lead to considerations for scaling commercialized digital transformation use cases across departments, plants, or regions in the enterprise.  

Employing a fast, sprint-based agile approach can aid with value realization and foster greater visibility into deployment items and action owners as they align with agreed upon requirements.

Beyond that, it is important to provide user training so the full advantage of the transformative journey can be realized. It’s vital to have a final acceptance and post system acceptance solution support, along with “as-built” solution documentation in place.

Phase 3: Evolve - Realize rapid value and impact

Following successful implementation, what’s next?

Scale commercialized digital transformation use case adoption across departments, plants, or regions in the enterprise to magnify the benefits across the rest of the organization.

Additionally, expand on initial digital transformation use case success to evaluate additional Industry 4.0 use cases that could provide immediate value. Manufacturers can consider concepts such as the digital thread, mixed reality, and autonomous operations.

Continue to monitor and manage change by aligning your growth and innovation with key personas and advocates and the tangible improvement KPIs achieved. By doing so, manufacturers can explore what can further improved and test out other ways to further maximize impact.

The reiteration of the steps previously fuels the essence of digital transformation and helps manufactures to continue innovating and evolving their enterprise even in uncertain times. Successful digital transformation supports an organization through fluctuations both subtle and massive – not only to stay competitive but to lead the way for others to follow.

Ready to begin? Rockwell Automation can help. Our digital transformation consulting team can work with you on a strategic plan that addresses priority use cases, business justification, change management, and an execution roadmap for technology implementation and support.