Driving Organisational Success with OKR Implementation
Insights and Experience from a Value-Centric Approach
Authored by Philip Hoyos , Director and Chief of Data and Analytics at Energinet ; co-author Jan B. Olsen , Owner of Jan B. Olsen Consulting / Better Change Fellow
The Danish Transmission System Operator (TSO), Energinet , has an ambitious goal to support green energy that will benefit the future of Denmark. Consequently acceleration in produced outcome is required to reach this target. This experience report shares the authors' efforts and experiments in creating a culture that focuses on value-added outcomes based on data-driven facts rather than solution delivery, with challenges encountered and lessons learned.
Target audience
Goal
Key takeaways from our experience with Objectives and Key Results
1. Introduction
This report outlines the transition of Energinet's Data and Analytics (DNA) department, aiming to offer insights applicable to large-scale transformations. The primary challenge is shifting the organisational mindset towards outcome-oriented collaboration, departing from traditional order-based dynamics.
Key challenges in this transformation include fostering collaboration, engaging stakeholders in processes, and promoting ownership, which are predominantly non-technical. These challenges often result in a disconnect between perceived needs and actual organisational requirements.
Transitioning to data-driven decision-making entails adopting established methodologies to provide automated, accurate, and timely information. This facilitates progress towards shared goals while enhancing organisational outcomes.
The transition begins with establishing a shared value-driven mindset within the DNA department. We employ a data-driven approach to gather and transform information, tracking progress towards Energinet's vision of Green Energy for a Better World.
This report details Philip's implementation of a value-driven approach using Objectives and Key Results (OKR) at the DNA Department, with Jan B. Olsen providing expertise and support. While Philip led this initiative, acknowledgment is due to all involved stakeholders.
Philip Hoyos, Chief of Data and Analytics at Energinet, brings extensive experience in driving data-driven initiatives. Collaborating closely with the management group, he spearheads the organisation's data strategy.
Jan B. Olsen, a consultant for DNA, has been instrumental in facilitating the outcome-focused transition, drawing from his expertise in strategic consultancy within complex organisations.
2. Background
Energinet, a Danish Transmission System Operator (TSO) and independent public enterprise, owned by the Ministry of Climate, Energy and Utilities, operates and develops Denmark's electricity and gas transmission systems. Its primary mission is to address the energy trilemma: transitioning to green energy while ensuring supply security and affordability.
Denmark aims for energy independence from coal, oil, and gas by 2050, targeting 76 MW of electricity from green sources by 2050, up from the current 9 MW developed over 40 years. Accelerating this progress is crucial, as depicted in Figure 1, which illustrates the gap between current levels and political expectations.
Energinet must support an additional 67 MW of renewable energy within 26 years, necessitating a radical change in approach, as highlighted in Figure 1. To achieve this, new methods are imperative, marking the beginning of this experience report.
2.1. Data and Analytics (DNA)
The Data and Analytics (DNA) department within Energinet's Tech & Innovation (T&I) division facilitates informed decision-making by enabling and governing data infrastructure, and transforming data into actionable insights through visualisation, storytelling, machine learning, and AI. DNA's focus is on delivering data-driven solutions to support decision-making across the organisation.
DNA has experienced substantial growth in recent years, with its workforce expanding from 22 to over 80 employees, and the number of teams increasing from 3 to more than 10. Additionally, the IT Department merged with the Innovation department to form Tech & Innovation (T&I).
3. The Story
In late 2020, Energinet's IT organisation underwent an agile transformation. Six months later, Philip was hired to drive a data-driven culture shift, crucial for navigating future challenges efficiently. Initial analysis revealed low data maturity and siloed practices.
This report highlights our transition from a solution-based to an outcome-focused approach, emphasising Philip's strategy of internal change. His method involves experimentation, learning, and applying insights to foster a data-driven culture. The overarching goal is to support Energinet's efficiency and meet renewable energy targets by 2050.
Key challenges include expediting results, enhancing data utilisation, and integrating data-driven decision-making into our practices. Success metrics are shifting towards process and customer-centric values, exemplified by Objectives and Key Results implementation. For instance, instead of measuring success by the implementation of an employee onboarding e-learning portal, we aim to improve employee onboarding time by X%.
3.1. The starting point
As a TSO predominantly staffed with engineers, we've embraced a 'fix it' mindset, which is commendable. However, there's a pressing need for better alignment and prioritisation of our core business challenges. This challenge isn't unique to Energinet but is pervasive across companies and departments.?
The issue stems from a lack of awareness of alternative approaches and time-critical constraints, leading to late collaboration between business and tech departments. This often results in a focus on delivering predefined outputs rather than considering their impact, limiting the potential of knowledge work, as highlighted by IBM Education's definition of knowledge workers: “a knowledge worker is a professional who generates value for the organisation with expertise, critical thinking, and interpersonal skills.” (IBM Education, 2023)?
Furthermore, there's a slower-than-expected adoption rate of deliveries, indicating a tendency to prioritise output over ongoing responsibility. This underscores the need for a value-driven approach with clear direction, alignment, and outcome focus.?
The order-giver's understanding of people, process, and technology often shapes the solutions provided to the order-taker, further constraining innovation. This situation is compounded by the urgency to promote renewable energy, exacerbated by the European energy crisis. Merely allocating more resources isn't the solution; we must work smarter.?
A shift towards customer outcome-oriented goals across the organisation is imperative. This will empower knowledge workers to collaborate closely with customers and make informed decisions, rather than providing temporary fixes. The following outlines our strategic approach to address these challenges.
3.2. DNAs journey to Objectives and Key Results
In the following section we will share Philip’s data-driven approach of using data to understand the current situation, outline the analysis and the following iterations from experiment, learn and grow.
Get facts to understand the current situation
We sought to support the missing direction and value-driven mindset to ensure an approach driven towards outcome and impact. To confirm our previous observation, we conducted a survey among the DNA department members to factor in their comprehension of DNA's purpose, goals, and impact. The survey results supported our initial observations: while people clearly understood DNA's purpose, more than half of the department members found the goals and impact unclear (Figure 2).?
In another survey (Figure 3), the DNA department members were asked about the principles behind the Agile Manifesto. Among other aspects, they were questioned on whether they were involved and interacted with the requesters and if they understood the value of the tasks they were asked to deliver. The responses were lower than the average for the entire survey, underscoring our observation that there was a lack of an outcome-based mindset. Instead, there was a tendency to assume the role of an order-taker.
This scenario is not attributed to individual shortcomings but is instead a reflection of the prevailing culture and organisational structure. Traditional project planning method tends to prioritise output over outcomes and can significantly constrain an organisation's agility.?
Analyse and reflect
The approach to measurement, emphasising deliverables rather than their impact or value, inadvertently restrains the organisation's innovative capabilities and responsiveness to change. By focusing narrowly on completing tasks rather than the broader objectives they are intended to achieve. Such a structure not only limits the potential for meaningful progress but also diminishes the motivation and engagement of team members.?
To truly advance, it is imperative to shift towards a culture that values the significance and impact of work, encouraging a more flexible, responsive, and outcome-focused approach to project planning and execution.
Set direction, experiment, learn and grow
With the observations supported by data, we set out to ignite and motivate a direction. We adopted an approach that invited everybody from DNA to take responsibility for how to create an impact instead of nearly focusing on delivering output.?
One team had already experimented with using Objectives and Key Results (OKRs). They struggled to reach their desired outcome, where their users would be happy with their offerings. At the same time, they aimed to limit the effort towards the highest impact with the accessible capacity. The team experiment proved successful in promoting a value-driven mindset and achieving the team's goals with customer satisfaction. It suggests that the OKR approach could be scaled across the entire department to achieve similar results.
Derived from the team experiment, our hypothesis was that by implementing OKRs across the entire DNA department, we would be able to achieve a similar result of a value-driven approach with clear directions and purpose. The assumption is that this should positively impact the department's previously mentioned observations. Focusing on the outcome instead of just delivering what is requested, we expect to see a mindset shift where people take responsibility for achieving the desired outcome. This means that our teams needed to understand:?
By having DNA members focus on outcomes, we expect DNA to take a more advisory role to business units by demonstrating the value creation and impact of work done with data. The teams would also need to engage the customers' strategic journey and transformation at an early stage to collaborate with the customer around the actual challenges and possibilities. This will eventually transform DNA from an order-taker with a fixed mindset to an advisor to the business, bringing data to the forefront and enabling data-driven decision-making that can be validated.
3.2.1. Getting started with OKRs
Let's discuss the concept of Objectives and Key Results (OKRs). First, Objectives that want to be achieved are set. The Objective should be a qualitative statement that tells what you want to improve. These Objectives are then addressed using Key Results (KRs). KRs are measurable metrics that show how close you are to the achievement and indicate whether or not you are moving in the right direction towards your Objectives.?
Usually, multiple Key Results are connected to one Objective. The focus is to move the Key Results by executing different activities/initiatives/experiments that are expected to do so. When an activity is executed but doesn't have the expected outcome, we move on to the next identified activity and execute that instead. The focus should be on delivering outcomes instead of just deliverables.?
In most cases, OKRs are set for a time range of three months, but they could also be shorter or longer, depending on the organisation's adaptability.?
OKRs should be linked to the overall organisational goals, meaning that the sum of each Objective needs to add up to the overall goals.?
Let’s try with an example:
Objective (A qualitative statement):
Key Results (Quantitative measurable metrics)
OKRs help focus on creating outcomes, set direction for what we want to achieve, and delegate decision-making power to team members who can take responsibility for achieving the outcomes. We see OKRs as the right approach to moving towards our desired destination for the future of DNA.
Department-wide experiment
The first step in the department-wide OKR approach was to formulate department-oriented Objectives aligned with the organisation’s goals and the IT and Digitalisation strategy, translate those KPIs into Objectives, align with the T&I management group, and liaise with key stakeholders from Group unit customers.
The primary focus should be on attaining the desired outcomes. To facilitate this, KRs were drafted by Philip based on the overall strategy, with input from the Enterprise Information Architect (EIA) as well as Agile People Leader (APL) and then collaboratively revised and aligned with product visions together with the Product Owners (PO) and Scrum Masters (SM). This process aimed to strengthen alignment and ownership of the OKRs in the DNA department. Team-level OKRs were established by these stakeholders to support the department's KRs, ensuring that we moved towards achieving the desired outcomes with our customers
This approach requires a shift to a value-driven mindset within the organisation and encourages people to think and act differently to achieve the desired outcomes. It also requires a cultural shift where people must think beyond delivering already-defined outputs. This approach is more about achieving measurable outcomes than just delivering outputs.
Let’s break down the steps:
This allows for moving the responsibility and ownership of building the road to archive the DNA OKRs and Goals to the team themselves.?
Objectives and Key Results alignment in collaboration
Analysis of feedback from the first two attempts indicated that we needed broader collaboration and alignment on the OKRs to succeed. So, we set out to establish company-wide objectives that, from a data perspective, would enable the overall goal. To succeed, the Objectives should be verified and aligned with the rest of the T&I management group and across all Group Units.?
Philip drafted three OKRs focusing on the overall goal with a timeframe for all of 2024. In summary and without diving into our organisation chart, these OKRs were drafted by translating company and customer strategic objectives into data objectives.?
The drafted OKRs were then evaluated and aligned in feedback loops:?
Together with his Agile People Leader (APL), Philip drafted an additional OKR focusing specifically on department development and that of our teams. These four OKRs became DNA’s Annual OKRs (AOKR).
To ensure continuous alignment with the rest of Energinet, we established a collaborative process to ensure mutual understanding of our OKRs. We also coordinated with other departments within the IT and Innovation department to align on shared objectives and shared KRs, particularly where there were dependencies across the organisation.
When dealing with multiple customers, everyone has their perspective on priorities and what should come first. This is true in any customer dealings. As a department, we are responsible for seeing the overall picture and balancing operations and development to benefit the overall department goal.?
To further the understanding of this challenge, we established a board with representatives of our key stakeholders with the task to prioritise the Key Results focus of each coming quarter and evaluate the previous progress. Each board member then had the task of communicating this prioritisation within their respective Group Unit. The working hypothesis behind the board? establishment was that this would:
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The above created a process, visualised in figure 6 (DNA’s OKR flow) below. This process helps DNA to break down the multi-year organisational goals into concrete annual objectives, Annual OKR (AOKR), establishing a direction for DNA members and its stakeholders.?
As described above, the AOKRs have their roots in the overall strategy. However, to ensure a shared priority and alignment across the data domain by each stakeholder, the AOKRs are aligned with the same stakeholders before every quarter to ensure a shared commitment. We have named these synchronisations Quarterly Business Syns (QBS).
To operationalise the structure, DNA teams meet quarterly to establish their own Team OKRs that support the AOKRs. To ensure that this is in sync across the department, we have the meeting on the same day for all teams well ahead of time, before the next quarter starts. The reason for meeting across teams is also to share celebrations and foster collaboration. The Team OKRs then naturally link into the teams' Sprint Goals and Planning.
Measure success in outcome improvements
To have success with OKRs, you (as a leader) must let go of the detailed control. Implementing OKRs fundamentally shifts the focus from technical-specific output to non-technical output, which gives the knowledge worker the ability to apply their knowledge to find the solution that will give the right outcome. It entails that you must trust each team and knowledge worker, in collaboration with the customer, will find the best solution to achieve a result.?
If you are unwilling to relinquish control, you will never succeed with OKRs. However, if you take a step back and reflect on it, you will have more control than ever. As your focus moves toward the outcome and impact achieved by your department, it will also be easier to communicate/translate progress to key stakeholders.
In reflection of the overall goal of accelerating outcome, giving away detailed control of deliverables greatly contributes to this objective. The closer collaboration and activation of the skills of the knowledge worker means that the right solution to the challenge is found faster, with impacts that may exceed expectations.?
Decisions regarding the right solution are moved closer to the experts and are no longer the measure of success. However, you are facing a different approach to understanding the progress of KPIs asked by upper management. You will properly have heard, “When will X be implemented?” where another change process needs to take place, so we really should be asking, “Have we improved process A by N%?”?
3.3. Result
In this section, we will focus on the results of our work and then gather our reflections and learnings in the following section: “Lessons Learned” In the transition to using an OKR approach, we saw a number of results that can be attributed to working strategically with OKRs.?
Clear direction and alignment
The initial observations showed that each team and employee must be able to see their contribution to the overall objective and understand DNA's impact on Energinet.
From the initial feedback and survey, we have succeeded with this through the work with OKRs. The surveys conducted on our teams have shown an increased understanding of DNA's impact on Energinet.
Improved processes to accelerate outcome
To underline the strength of working with OKRs, the following example will outline what can be achieved. Our internal OKR focused on improving DNA as a workplace. One of the Key Results, to this objective, had a target of enabling new employees to deploy to production within 10 working days to establish the feeling of being able to add value towards the overall goal quickly.
This meant that the current process and time to deployment had to be outlined across teams before improvement could be made. The best result showed a 91% decrease in onboarding time from 22 days to just 2 days, and all teams managed to get below 10 working days. Directly derived from focusing on this, OKR teams identified automation opportunities as process obstacles to be eliminated. Another great example was the focus on automation, which meant re-establishing a deleted service decreased from 8 to less than 2 hours.
Cross-departmental collaboration
In an effort to accelerate the outcome, we brought team members from DNA together with those from another Group Unit’s department to form a cross-departmental team focusing on utilising the domain knowledge from both sides of the table.
After the initial stages of Storming and Norming in Tuckman's Model of team development (Tuckman, B., 1965), the team reported an increase in outcome. From our side of the table, there was an increased understanding of the business side. From the business side, they reported that working with data in an analytical context using the services we provided exponentially increased their efficiency. As one of the team members said, “I'm no longer able to go get a cup of coffee from the ground floor or even from the machine on the third floor where I’m working, as the [data] query is completed in a heartbeat.”
The result:
Employee satisfaction increased, and churn decreased
In the annual employee satisfaction, there has been an increase across all teams and those directly referring to Philip. This increase happened while DNA underwent a significant number of challenges:
In the same period, the churn of DNA decreased compared to that of the rest of the organisation and comparable departments.
Factual progress insights
To enable understanding of the impact we contribute, we have added new information-overviews to track, monitor and/or analyse essential aspects of our operation and how we work, in essence to understand the process that we are supporting:?
In this, it is essential to use existing tools and automate the data processing and visualisation to gain insights from established ways of working without adding new steps for the sole benefit of tracking.?
We started on paper with handheld reports to quickly understand what would improve our data-driven journey. The next step was to gather the data that would work as an analytical base for our insights. Some of these are readily available, but others must be developed to ensure that data is collected automatically. Currently, our teams are working on a digitised dashboard that will automate the prioritised measures. Through iteration, this will improve over time.
Once all of these information-overviews are developed, the rest of the T&I organisation can essentially use these information-overviews as long as their daily way-of-working use the same tools in their daily work. Apart from being automated and standardised, these tools enable us to analyse usage, be proactive and follow up with the customer. It also allows for historical analysis to understand “what happened” and, even more importantly, be able to collaborate with users on “why did this happen” so that we can work towards a future of prediction “when will this happen”.
Continuous organisational improvement
To reap even more benefits, Philip made efforts to inform group units, and management about the transition to OKR and the progress and demonstrate our methods, models, and achievements to the rest of the organisation, particularly within T&I, and to key stakeholders. This had several benefits; 1. It is easier to change simultaneously and share experiences of what worked and what didn’t, 2. If everyone is working with the outcome has their primary objective that will help us achieve the same goal together.?
At the time of writing, adopting an OKR approach has spread so far as to be established by the management group for 2024 at the T&I level. With the work we have done so far and the learnings we have had, we are already in the 'game'. Our AOKRs are comparable to those goals set for T&I.
4. Lessons Learned
We learned a lot by experimenting, continuously getting feedback, and implementing, and we have included the most important learnings here.
Change takes time - take time to change
From the birth of working with OKR, first as a small-scale experiment to a department-wide transition, was executed in a relatively short time. This also meant that we had been in the process, through the material and theory, and over the plan many times. The first transition attempt was not a complete success nor a disaster. Enough evidence presented itself to show that this was the correct course of action.?
Applying the ADKAR model helped us in the transition and the steps to inspire each individual towards the overall goal (Hiatt, J., 2006). In the first attempt, we did not spend enough time providing knowledge on how to change. Fixing this step and thoroughly walking through each step of the ADKAR model with Product Owners, Scrum Masters, and the teams both on a team level and in our Quarterly OKR (QOKR) sessions anchored the change.
Enabling factual understanding of change is necessary to understand progress
The information-overviews that are under development in the DNA department will help the teams to understand the impact of their activities towards the KR. In reflection, these information-overviews should have been developed from the beginning or very early after the organisational transformation to an Agile approach.?
Insights into process steps and main KPIs through automation provides insights on a daily basis and is essential for any operation that wants to accelerate change. A we shift the mindset towards an outcome-based impact, the need to understand the impact has fostered the need for automated information-overview to enable insights, and these tool will support that. Better late than never.
One organisation and two systems is a bad idea
An organisation should not utilise a parallel system, e.g. project funded together with OKRs. This adds another dimension of complexity to the existing system. Furthermore, as long as funding follows the one system, that system will always win.?
Despite the added complexity, we did exactly that, and it mostly worked out. The reason it works is based on an intense and open dialogue with stakeholders about their needs to succeed, meaning that the objectives that have been established fit with what is expected while still setting up the freedom to find the best solution to reach the agreed outcome.?
Establishing fundamentals is necessary
The larger the organisation, the harder it is to hinder parallel work from occurring, and maybe it shouldn’t - that is a debate for another day. Suffice to say that to accelerate the outcome, the hypothesis is that we need less parallel work, more collaboration and clear processes to understand who is doing what and where to impact whom. In this, there are two main challenges to be addressed; 1. Outside the department, and 2. inside the department. To enable a faster transition, the following needs to be established and implemented across the organisation:
Each responsible member of the IT management group drafted several principles for formulating the IT strategy. These principles should establish mandates and/or rules for how to do certain things and help address the first of the two challenges.?
As responsible for the data-driven part of the IT Strategy, Philip formulated three principles on data to support the journey for the whole company. These principles established a mandate across the company and helped communicate how data should be handled and by whom.
Addressing the second challenge from a departmental perspective, with a rapidly growing organisation, we also need to ensure we do not do any parallel work. With that in mind, we took time to:
Implementing OKRs - experiment, start small, then scale up
In the process of adopting OKRs, we started with one team to get initial findings and experience. This was a great approach with several benefits of learning do’s and don’ts. Taking this to the next level on the whole department was quite a mouthful as this was the first step in having two ends meet; 1. the ompany strategy and? 2. the department transformation.?
Starting with the latter, the department transformation took several attempts before taking on. The major challenge is that change takes time, and thus to establish clear information and a guided process to enable this change to anker faster. This is a summary of the major learnings:
Establish Shared Objective and break down Key Results into team scope
The other side of the equation, the company strategy, was quite a bit harder. Given the nature of our organisational structure and how each Group Unit works as a subsidiary, other factors had to be considered. However, having a departmental view of OKRs is not enough to succeed. Everyone needs to have shared objectives from the overall strategy.
To bring our key stakeholders on board with this approach, Philip informed them early. He introduced them to OKRs to give an understanding of the direction we were headed and that the goal was to enable acceleration. This is a summary of the major learnings:
In the process, we added new benefits that indicated OKRs to be the right course of action. At the time of writing, these are the highlights:
When not to use our experience
To adopt the changes and implement objectives, a mindset change is needed. It is not enough to establish some objectives and ways to measure these; what is needed is a mindset change, a change that is hard to implement. The challenge here is whether the surrounding organisation still expects an output focus, as this has been an innate way of measuring success for most people.?
It requires leadership, dedication, a lot of communication and close collaboration to challenge the established ways of working and allow people to find new ways to fill the space that has been created for them. The easiest thing to do is to fall back to what is known and continue to do what the organisation expects of you. If this happens, you will surely lose any opportunity for change.
So, if you want something where you just can measure leading indicators of deliveries, but do not want to change mindsets toward outcomes, you should do that and not focus on a change in mindset. It will save you from headaches and an initial slowdown in deliveries.
5. Acknowledgements
Philip acknowledges:
To all of the members of DNA, I would like to extend my gratitude for being open to change and for all the changes that you have implemented so that each of your teams can work towards our common goal. Thanks especially for reaching out with concerns, suggestions, and good stories about your success.
Especially thanks to Anders Kn?rr Lyseen and his team for bringing my attention to OKRs and being the first to experiment with this approach.
I am immensely grateful to my staff, Agile People Leaders as well as CPO's and Bj?rn Therkelsen , Enterprise Information Architect and the Product Owners for their support in creating the vision and their hard work with both OKRs as well as the transition of all of DNA.?
I would also like to extend my acknowledgment to DNA’s Scrum Master, who has facilitated and made the transition easier for DNA's teams. The great work they have put into team and customer surveys has helped gather the data necessary for a data-driven team approach.
To all of the members of DNA, I would like to extend my gratitude for being open to change and for all the changes that you have implemented so that each of your teams can work towards our common goal. Thanks especially for reaching out with concerns, suggestions, and good stories about your success.
Every change requires the support of one's leaders, and I would therefore like to express my sincere thanks to Signe Horn Rosted and Nicolaj N?rgaard Peulicke for their support.
Finally, I would like to give a heartfelt thank you to Jan B. Olsen , DNA external consultant. You have been an invaluable team player, supporting and guiding with your expertise in both Agile and OKR. You excel as a facilitator, and with your expertise, we have had a much shorter and smoother transition to working with OKRs.
To all of you, thank you. As a team we have succeeded in progressing DNA and thus moved one step closer to accelerating outcomes for the benefit of Energinet and Denmark towards a greener future.
Reference
Energinet Strategi (2022, December). https://energinet.dk/media/xjab2ool/energi-til-tiden-2022.pdf , pp. 10.
Energinet Organisational Chart: ?https://energinet.dk/om-os/organisation/organisationsdiagram/
Hiatt, J. (2006). ADKAR: A Model for Change in Business, Government and Our Community. Prosci Research.
Lewis, K. (2023). Navigating Digital Transformation: The ADKAR Model for Effective Change Management Introduction. Retrieved from LinkedIn: https://www.dhirubhai.net/pulse/navigating-digital-transformation-adkar-model-effective-karen-lewis/
IBM Education. (2023, July). What is a knowledge worker and what do they do? Retrieved from ISM: https://www.ibm.com/blog/what-is-a-knowledge-worker-and-what-do-they-do/
Tuckman, B. (1965). 'Developmental sequence in small groups', Psychological Bulletin, vol. 63, pp. 384–99.
really a good topic.
Agile People Leader | Empowering teams and individuals to create meaningful change through collaborative work
6 个月This is a treasure trove of insights for anyone looking to work with OKR’s in a large and complex organisation. I appreciate the emphasis on dialogue, involvement, focus and improvements along the way. It really does reflect, what I have experienced being part of the later stages of this drive for organisational success. Thank you for sharing!
Philip Hoyos - great article and perspective on the DNA journey with all the fantastic people at DnA??.
Certified Coach & Organisational Change Specialist | Helping Businesses Realise Their Purpose and Goals
6 个月It was an enriching experience to co-author this report on Energinet's transformation through OKRs. ???? Our journey to shift the organisational culture towards a more value-oriented approach has been enriching. I believe that the insights we've shared can help other organisations navigate similar transitions effectively. I'm looking forward to seeing how others apply these principles in different contexts and hearing about their challenges and successes. Let's keep pushing the boundaries on what can be achieved with data and OKRs in the energy sector and beyond! #DataAnalytics #OKR #Leadership #Transformation #Energinet