Maturing a Data Literacy Initiative in a Large Organization
As we left off in the previous article stating that a new Data Office was established, it is now time to take a closer look at how this Data Dream Team is setup and which role it plays in the further development of the Data Literacy initiative.
Again, what started as a data literacy experiment by a couple of very passionate colleagues, gained momentum in the organization over a short period of time. This was clearly shown by the interest among colleagues across the company as the number of members signing up to the community and the numbers of visits to the internal site exceeded our expectations.
So where are we now and what has happened since the last article was published? Read on to learn what role the leadership and organizational setup play for the data literacy initiative to continue, how we plan to further develop the data literacy journey and how we are trying to understand our target group even better.
The Data Office
To help all LEGO® employees unlock the value from data, a central Data Office has been setup. This Data Office plays an important role in the company-wide digital transformation, and thus focuses on making data a first-class citizen, equally important to engineering and architectural structures.
For the Data Office to help enable the entire organization make value out of data, it is important to understand that a large company like the LEGO Group has an enormous amount of data across a full value chain. This means data objects are generated and utilized all the way from design and development through marketing and production to sales in our own and customers’ stores physically as well as online.
The Four Principles
With such a wealth of data across business processes, we need to be able to navigate in the data landscape and understand the potential for insights and innovations it can bring.
Therefore, the Data Office has been organized around these four principles:
1. We Build Trust in Data
2. We Look After Our Data
3. We Build Data Science Products
4. We Enable Data Intelligence
Firstly, for employees to increase the use of data in their work, they need to be able to trust the data. Thus, the Data Office will focus on building solid frameworks on Data Literacy, Data Ethics and Data Governance. This is to enable the wider organization to better understand which role, they play to make sure we generate, look after, and use data responsibly. As our Chief Data Officer has expressed in a podcast (https://www.linkedin.com/feed/update/urn:li:activity:6865942062764703744/) and several interviews, Data Ethics and Literacy is for everyone across seniority levels and Data Governance is similar to brakes in a car; not in place to slow you down but to enable you to go faster in a safe manner.
Secondly, to support the frameworks, principles and guidelines all related to building trust in data, naturally also comes a need for scalable and trustworthy data platforms. Thus, the Data Office aims to build and deliver stable and easy-to-use data platforms. These platforms must cater for very different data use cases like e.g. self-service ingestion of data sources, easy administration of data life cycle, quality, and access management, as well as the ability to build new data products.
Thirdly, the Data Office also houses the Center of Excellence within Data Science. This highly specialized team of data scientists and machine learning engineers all work together to develop and mature advanced analytics products like e.g., algorithms which can predict and forecast supply chain demand as well as the effect of certain marketing activities.
Finally, the Data Office is also striving to enable the practice of Data Intelligence across the LEGO Group. We define Data Intelligence as the generation, maintenance and use of KPIs, standardized metrics, business intelligence, dashboards and reports. To help all the LEGO Group employees become even more self-sufficient in practicing Data Intelligence, the Data Office will work towards offering colleagues relevant front end data visualization tools and a data catalogue displaying the packaged and summarized data sources and metrics to be used.
Summarizing, the Data Office wants to enable all our colleagues to build trust in working with data across different skill and capability levels. If you are curious to learn even more about how our Chief Data Officer envisions a data dream team, check out a recently published soda podcast right here:
https://www.linkedin.com/feed/update/urn:li:activity:6865942062764703744/
The Data Office Team Structure
Below is an overview of the team structure within the Data Office.
The different teams have focus areas and responsibilities, but all of the teams need to collaborate across in order to succeed together on making the 4 principles a reality in the LEGO Group.
Connecting Data Literacy to the Four Principles of the Data Office
With the Data Office established and the Four Principles set, a question to the Data Strategy & Communities team, who focus on Data Literacy, could be:
How might we continue our approach to deliver a Data Literacy learning journey matching the Data Office purpose to help unlock the value of data?
Remember, we have defined Data Literacy as the ability to read, understand, create and communicate data as information, and this fits well into the 4 Principles described above. All the principles described above support, in each their specific way, the end goal of enabling all our colleagues at the LEGO Group to get value out of data in their daily jobs.
Thus, to ensure that a data literacy initiative is appealing and suited to a large group of employees representing a broad spectrum of skills and proficiency levels in working with data, we need to understand the composition of our target group. And very importantly, we also need to understand the type of problems or real-life use cases they are trying to solve.
Who is your Target Group?
In a company with more than 20,000 colleagues, it can be difficult to divide people into certain categories or segments, as there will always be some that don’t fit into a certain box. Also, it is very key for us that we do not want to place people in boxes, and then simply dump specific content on them which we think maybe is relevant to them.
However, to structure the different elements of the data literacy initiative, we do need to create an overview for internal use in our team, which is to be used as a high-level indicator for content curation to specific personas.
To get us started on defining the different personas, we have found good inspiration in the Data Literacy Persona Framework from Gartner, developed by Alan Duncan. Below is a link to the framework.
https://www.gartner.com/en/documents/3998775-tool-data-literacy-personas
In essence, the Gartner framework highlights and supports our understanding of data literacy being a central capability in the intersection of people, processes and technologies in today’s digital environment. Obviously, not everyone needs the exact same level of data literacy to succeed, thus thinking about which different personas exist in an organization is a good way to better understand your audience.
The Gartner framework suggests 5 main personas, from hands-on analyst to executive leadership. In addition, these main personas contain 26 sub-personas in total, which all are described in detail on specialties and expectations.
Approach to Understand our Target Group
To keep our approach simpler, we have chosen to view our target group from the lens of the 5 main personas. To be sure we then consider all the important aspects of the 26 sub-personas, we have read through all the detailed descriptions of these and chosen to extract what we see as key specialties and expectations of these. This extract has then been used as input in our own persona format, in which we also have added our own defined expectations like e.g., ‘understanding company operating model and high-level processes’. We regard knowledge of business operations and processes as very important elements in any data literacy initiative alongside mastering technical tools and data transformation methods. Without business understanding, how would a data practitioner be able to understand and critically question the specific data extracted and used in designing applications, reports, dashboards, algorithms?
Now, with the personas defined, we have two next steps to take. One step is to map the current employees according to these personas. The purpose is for us internally in the team to create an overview of the size and distribution of the 5 main persona groups, so we can develop relevant and targeted communication material to them about our data literacy offering. Another step is to design a data literacy learning journey for the different persona segments.
Inspired by the sometimes-thought-provoking Nick Shackleton-Jones, who wrote the book ‘How People Learn’, we need to understand what challenges our colleagues face and what they care about. We believe that what makes people curious and interested in learning, is creating experiences in which they find themselves needing to solve a challenge and then they will look for resources to help them solve the challenge. How to then create these experiences and make sure we reach out broadly in the organization?
This is where the Data Office structure and the 4 Principles again come into play. We need to collaborate internally in the Data Office to create and curate learning content and experiences for all our colleagues in the LEGO Group, and to promote widely how the different services from the Data Office can help them tackle their data challenges and opportunities. Obviously, this requires insight on what matters to our colleagues, and we aim to uncover this by among other things to run a survey across the persona segments in quarter 1 2022.
However, not only do we need to collaborate within the Data Office to establish a solid data learning journey, but we also plan to join forces with our HR function in the LEGO Group. This partnership with our People Operations and Development department is an important step towards formalizing what started as an experiment to now evolve further into being a crucial part of how we onboard new data practitioner colleagues as well as how we keep focusing on the ongoing data learning in the organization.
Data Literacy could be a lever for Career Opportunities
With the ambitions of the Data Office and the associated services and products to be provided in support to the four principles, we wish to experience positive impact not only on business outcome but also on the career opportunities for all of us working in the LEGO Group. Imagine the opportunities for different career development paths in an organization where employees are inspired to learn from each other as well as enabled by solid data foundations and data literacy experiences.
A Year Full of Exciting Challenges to Tackle
To end this article with a couple of key messages for the reader; here are a couple of learnings. We have experienced in practice that a data literacy initiative can start off as an experiment by passionate people and succeed to reach a broad audience. However, it is important to have leadership support and focus to ensure it is further matured in a large organization.
We look forward to continuing our journey here in 2022, where we will focus on building more understanding of our target group and what data challenges they are trying to solve. Also, we will dial up the collaboration with our HR function even more to ensure the data literacy is professionalized and embedded in the company’s people development strategy.
Finally, we still need to keep engaging and collaborating with all our data practitioner colleagues who indeed is a source of great knowledge. With their engagement, we can internalize and showcase experiences, best practices, share cheat sheets, guidelines, learnings and much more from working with data in all levels from standard reporting to development of advanced algorithms, all in a LEGO® context. We believe that inhouse knowledge is one of the most important parts of the data literacy initiative. While there are a lot of possibilities for purchasing external training platforms these can help build a generic basic knowledge, but these cannot stand alone.
Thank you for reading.
