Digital transformation (DT) has become a common conversational theme in the industrial and academic arenas. Plenty of articles have been published describing the urgent need to embrace DT initiatives, as well as the potential benefits of doing so, yet many of these articles fail to offer a clear implementation strategy.
Limited guidance has been provided about how to materialize these opportunities, much less so in a systematic and consistent manner. The thoughts on DT have missed an important consideration: the delineation of the strategy required to materialize the benefits promised by the technological revolutionary era called digitalization.
The strategy to embrace digitalization should be developed and tailored to the nature of your business and specifically address your final goals and objectives.
The definition, implementation and consolidation of a DT process should go beyond the selection of the technology and cover soft elements, such as a clear vision and the definition of objectives and strategic approach, including leadership, culture, governance, etc.
As with many other initiatives, one way to systematically implement DT is through the define-plan-implement-evaluate-feedback (DPIEF) cycle:
Define – What should be addressed and achieved through DT? Outline the goals and objectives, operational context, scope, and general implementation strategy. Basically, define the what and the why, which should be coherently aligned and supported by a clear vision.
Plan – The execution of the DT initiative is planned by identifying the activities and resources needed to accomplish the goals, along with their respective timelines for completion. In other words, define the how and the when, which should be considered as a trade-off between the present and the future, nurtured and molded by the vision and the resources available.
Implement – Each one of the tasks and activities as stated in the plan are implemented. This includes the compilation, categorization and validation of the required data to track the progress of the plan and make informed decisions that could improve results. Key aspects of this phase are the presence of inspiring leadership and an agile organization.
Evaluate – Review the results and compare the preliminary results with the objectives and goals identified in the previous stages, emphasizing the trend toward the achievement of these objectives and the consolidation of the vision.
Feedback – Provide feedback and continuous improvement by identifying lessons learned and proposing measures to correct any potential deviations, manage risk, and improve the value added. This stage should take into consideration the achieved progress, resources, predominant culture, and organizational climate.
The DPIEF cycle, further described in the following sections, depicts a scenario of operational excellence (OE).
Figure 1: The DPIEF cycle
Define Phase
The define phase represents the foundation of the process and denotes what wants to be achieved. If your objective is achieving OE, you need to break down what OE means to your organization in terms of quantifiable objectives. The OE objective, which may be the starting point for more rigorous and holistic organizational objectives, should be aligned and supported by a corporate vision. This vision may evolve as stakeholders’ needs and market conditions change.
The define phase includes, but it is not limited to:
- Set DT goals and objectives (value promised);
- Characterize operational context (internal and external factors);
- Define the scope and its impact on people, processes, and the whole organization;
- Identify requirements (e.g., data, tools, training, etc.);
- Develop the implementation strategy (pilot project, overall initiative, etc.);
- Identify success factors, including key performance indicators (KPIs) and key risk indicators (KRIs).
Before embracing a DT initiative, the organizational goals and objectives should be clearly defined.
The following sections provide more details to address these major tasks and activities.
Organizational goals and objectives
If you are pursuing OE, a clear understanding of it in terms of safety, productivity, sustainability, etc., is necessary; simply stating that this initiative is being implemented to meet the company’s safety objectives is not enough. If it means to reduce the occurrence of occupational and process safety related incidents and accidents below certain threshold levels (or, alternatively, reduce emissions), you need to define it clearly and consistently, including initial targets.
Similarly, what is meant by productivity, sustainability, or any other attributes included in your objectives must be explained and internalized, and these definitions should be aligned with the adopted organizational and corporate vision. Additionally, for each one of these key attributes, appropriate data requirements and KPIs should be defined.
Operational context
The operational context of the organization must be characterized, including, but not limited to, understanding the:
- current organizational challenges to deploy DT;
- organizational climate and culture;
- potential legal, political, social and environmental factors that may impact this initiative;
- organization’s capability and competencies to implement this initiative.
It is also important to identify what similar companies and competitors are pursuing through digitalization (e.g., industry experience implementing similar initiatives).
Scope
The scope should cover all the elements required to achieve the defined objectives and goals, and should consider the changes at the people, process and organizational levels. Defining these requirements is vital to having a clear picture of the operational context.
Understanding what set of data, tools and training are needed and for what purpose
A variety of data and tools may be needed at different levels of the organization, structured through a robust and consistent data management framework.
Tools may be required to collect data in a more efficient way, to clean and validate the collected data (e.g., data reconciliation), and to analyze the data. These tools, along with the data management framework, will transform the data to information and, ultimately, to knowledge that can be used to make better informed decisions (i.e., data-information-knowledge framework).
Depending on the current automation infrastructure and data management systems, the level of effort and resources needed to collect and clean the data could be enormous, particularly considering the volume, variability and veracity of the data. Therefore, careful determination of what data is actually required is key. This is not a simple data digitalization exercise; emphasis should be given to the data required to make sound decisions to continually improve asset performance. This effort should be complemented by defining KPIs that ease the analysis and understanding of the performance and health of the asset and asset management system.
The emphasis should be on collecting data that can be utilized to improve asset performance toward fulfilling your OE goals and objectives.
Implementation strategy
The implementation strategy should define the general principles and approach to materialize the value promised. It should consider, on one hand, the operational context and scope (e.g., people, processes, organizational climate and culture, etc.), and on the other hand, the eagerness and willingness of the organization, particularly top management and executives, to embrace DT. Depending on these key aspects, the implementation strategy should address the following:
- Can this initiative be implemented progressively within the whole organization or is starting with a pilot project a more appropriate approach?
- How should the required changes on people, processes and culture be addressed? The main focus should be on leadership, skills and, eventually, the business model.
- What adjustments on the governance system are required to facilitate the implementation process? Can the DT promote a safe and cooperative environment and reduce the organizational vices and silos?
- What technologies may be required? What will be the best way to integrate these technologies into our processes in a more cost-effective and seamless manner?
- If the existing processes must work concurrently with the proposed one (at least during the transition phase), how can the interfaces, conflicts and potential discrepancies be managed, etc.?
- What other support functions are required to ensure fulfillment of objectives?
- What is the best approach for the company: a new organization and a designated chief digitalization officer or smaller but coherent DT teams across all organizations (a top-down vs bottom-up approach)?
- Is the support/advisement of third-party consultants required?
- Are there low-hanging fruit opportunities that can be leveraged (i.e., quick wins)?
- What is the best way to implement this initiative with the resources available?
- How can you measure if DT is evolving as expected and whether the changes in people, processes and culture taking place are going in the right direction and at the expected change rate?
Key success factors and potential risks
The KPIs must be defined so they can be measured and the progress through the DT journey tracked. The use of KPIs contribute to evaluating the progressive fulfillment of the initially stated objectives. As previously indicated, a data-information-knowledge framework should be defined to link the data at different levels of the organization and at different subprocesses to the final set of KPIs that characterize the organizational objectives.
A system to identify any potential risk and/or showstoppers, including KRIs, must be defined. It should address those events that can compromise the initiative and, if there are any, evaluate the appropriate preventive and mitigation measures to manage them.
In summary, the main objective of the define phase is to be clear on the DT objectives and be able to define the value promised, as well as identify and validate the inputs required to develop the implementation plan.
Plan Phase
The plan phase should encompass a clear picture on how to implement the strategy: How long will the transformation take? What resources are needed to implement the DT and evaluate progress? What is the sequence of major activities (road map)? How will the activities/tasks be implemented and their potential interfaces/interaction managed? What are the defined roles and responsibilities? How will KPIs and KRIs be assessed and monitored?
The plan, at a minimum, should address the following:
- How and when the data will be collected, validated and used by the different users?
- How and when the KPIs will be assessed, monitored, tracked, and opportunities for improvement identified?
- How and when the KRIs will be assessed to allow for early identification of potential risks and/or showstoppers that may jeopardize the value promised?
- What the infrastructure requirements are, including hardware, software and human resources to collect and validate the data? This data should be transformed from raw data to conventionally operational and maintenance data, to valuable information, and ultimately, to knowledge.
- How and when the organizational climate and personnel engagement in terms of attitude, mindset and aptitude (e.g., capability and willingness to change/succeed) will be addressed to enable, consolidate and enhance the implementation of the data-information-knowledge framework?
- How leadership will be consolidated and champion(s) identified to promote and support this initiative and inspire people?
- What will be the roles and responsibilities of key players responsible for executing, coordinating, and monitoring the DT initiative at different levels of the organization/company?
- What is the time frame to implement the data-information-knowledge framework, including the implementation of KPIs to evaluate the change rate and maturity of this initiative?
- An implementation schedule with milestones to be used as a reference to track progress during the implementation phase.
Enabling, consolidating and enhancing the implementation of the data-information-knowledge framework are vital to ensuring the success of DT initiatives.
Implement Phase
The implement phase represents the to-do portion, where all tasks and actions identified during the plan phase are implemented, including, but not limited to:
- Implement the organizational changes, if any, to remove any silos or organizational obstacles that can compromise the DT initiative.
- Establish the infrastructure (hardware and software) required to collect, validate, use the data and, ultimately, get KPIs to monitor, track and identify opportunities of improvements. This infrastructure also should be used to assess KRIs early in order to identify potential risks and/or showstoppers that may jeopardize the value promised.
- Establish the organizational resources (e.g., human resources, processes, procedures, etc.) to collect, validate and use the data, and transform it from raw data, to conventionally operational and maintenance data, to valuable information and, ultimately, to knowledge.
- Promote the required changes in behavior (e.g., attitude, mindset, aptitude, etc.) to enable, consolidate, and enhance the implementation of the data-information-knowledge framework.
- Establish the mechanisms to monitor and track the DT implementation process.
- Collect and validate preliminary results.
- Track progress and changes toward OE through the defined KPIs.
- Communicate preliminary results and promote personnel engagement.
- Ensure that:
- Ongoing decisions are consistent with organizational goals and objectives, particularly related to OE;
- Potential risks and showstoppers are appropriately managed;
- Lessons learned from previous DT initiatives are considered.
Evaluate Phase
The evaluate phase represents the analysis and assurance stage, where all tasks and actions are implemented and personnel behaviors and asset performance changes are evaluated to determine if the DT is effectively helping the company move toward the fulfillment of the organizational objectives. During this phase, the effectiveness of the strategy and plan, as well as their implementation, should be assessed by:
- An increased focus on understanding how value has been added.
- Analyzing the data and identifying patterns that can be used to improve asset performance. In OE, it may involve:
- Identification of failure patterns and behaviors, and risk event precursors;
- Understanding failure modes and mechanisms of failure before their occurrence, providing feedback to the design team/system providers on how to create designs not susceptible to the identified failure mechanisms and/or more tolerant to faults or damage;
- Optimization of inspections, testing and preventive maintenance (ITPM) tasks to improve asset performance;
- Identification of more suitable process operation practices, including optimal operational envelopes to improve efficiency and throughput (e.g., to reduce the occurrence of failures caused by operating out of the design and safety limits).
- Identifying potential deviations from the initial plan and their impact, and evaluating the paths forward.
- Collecting findings from the different digitalization initiatives carried out in order to provide evidence of performance achievement and communicating this achievement in a formal document.
- Documenting to what extent the organizational objectives and requirements have been met.
- Providing a clear picture of the current initiative status.
Feedback Phase
The feedback phase represents the continuous improvement stage, where, based on the analysis of the results, the action plan is adjusted and improved as necessary to move toward the fulfillment of the organizational objectives. During this phase, required changes should be identified to optimize the used data and resources toward OE by:
- Increasing the focus on understanding how value can continuously be added;
- Documenting and implementing lessons learned;
- Incorporating these lessons learned and new findings to the DT process to increase its effectiveness; This may involve adjustments on:
- Operational context;
- Human behaviors and personnel skills;
- Data and tool requirements;
- Governance and organizational climate;
- KPIs and KRIs.
Moving toward optimizing the use of the data-information-knowledge framework will require an increased focus on understanding how value can be added.
The different interests companies and organizations have in establishing DT to realize the limitless potential it has to offer requires a tailored strategy and an adaptation of the digitalization process to the nature of business and, particularly, to corporate objectives. For example, in the energy sector, which is characterized by complex physical assets, digitalization is recognized as a catalyst that speeds the consolidation and performance of OE initiatives.
The DPIEF cycle represents a consistent and well-structured framework to continuously implement DT by defining the what, why, how and when. This approach provides the mechanisms to evaluate the progress and stay aligned to the initially stated goals and objectives, and make the adjustments required to fulfill and materialize the value promised.