Called to lead the profound organizational changes brought about by the digital transformation, Human Resources departments are facing a historic passage in which the corporate culture, inspired by the concept of People Management, has become more and more a community culture.
Beyond Digital Dexterity, or the ability of people to easily maneuver in a digital environment, the culture that is formed around corporate innovation consists of several elements.
In a context of continuous acceleration of change, made even more complex by Covid-19, leading the evolution of relationships and business processes to align with the characteristics required by the digital culture represents the challenge of this decade.
To understand the extent of the impact of the transformation on non-digital companies, let's consider, for example, how much the conversion from in-office to remote-collaboration and the consequent conversion of collaboration channels from offline to online has challenged companies worldwide.
The digital transformation of a company should be considered as a race for its life or death. Reaching the finish line means having successfully restructured the corporate DNA, having assimilated anew strategic structure before it is operational. It means having managed the complexity in the evolution of skills, in the emergence of new professional roles, in the profound and timely redefinition of the very concepts of 'working space' and 'organizational model'. The adoption of a digital culture capable of enabling each person who builds corporate value for such changes is a challenge that can only be won through an approach with vision and speed of execution on a large scale.
In approaching to elaborate this newDNA, it is inevitable to start with the meaning of the company. In considering it first and foremost as an entity based on information in which the balance and the true survival capacity lies in the ability to feed on the wide spread element of which the entire global economic ecosystem of this century is immersed, now no longer only physical or digital, but hybrid: data.
How are structures from automation, prediction, data-based business execution designed and implemented for this purpose?
Read all about Spindox Bixuit's DataThinking Framework.
Offering the design of digital transformation to the market, from the creation of B2C business models to the reconfiguration of B2B processes, in 2020 a global fashion player posed a challenge to us. As part of an ambitious digital transformation of the group that has over 6,000 employees, a turnover of 1.53 billion euros in 2019, which grew by 2.6% in a complicated year, we delivered a B2E training and empowerment program aimed at creating a corporate data culture.
The operation has allowed us to converge our experiences relating to the design of digital ecosystems - as carried out for example for SIAE and relating to the design of support for PeopleManagement for companies in the fashion sector, in a new dimension in which the data realises its information function to evolve into a new formative dimension.
The program is based on the Data Thinking approach and allows us, thanks to an Academy made up of pre-selected participants from the company and design sprints involving its HR,IT, and Innovation departments, to inject the mindset that it needs for it to evolve.
In carrying out this program, we thought of learning by doing paths and participant engagement strategies.It is a model that can be applied in other circumstances where it is necessary to fill a lack of skills on the part of employees and create a strong corporate culture.
In its canonical definition, data is a simple and coded description, which can represent information taking different forms: numbers, letters, images, video, audio, etc.
In computer science, data refers to a value that is expressed in bits. Digital data is the object on which the algorithm intervenes, a sequence of elementary steps that allow information to be processed.
Therefore, the term "data" does not in itself indicate information. The latter is the result of data processing.
In summary, data is a raw element that must be processed and contextualised to become information. Information is the result of the interpretation of a set of data, aimed at increasing the knowledge of a subject about something.
Why this digression?
Because information produced and assimilated by the recipient, in various forms, has the ultimate goal of being useful in a decision-making process.
Isn't that what you’re interested in as well? Making the best possible decision?
[The COVID-19 organizational reset]
"... requires CEOs and other leaders to be knowledgeable enough about data and technology to be able to make informed decisions. The chief information officer, the chief technology officer, marketing—every decision is now powered by a set of data and analytics that you have to understand quite deeply."
– Dame Vivian, McKinsey Senior Partner London, Business in 2020 and beyond
DataCulture is a real mindset that allows a company's professionals to see and recognise the value in the information built from data.
Underlying a data-driven company that considers data management a strategic pillar of the business, is the ability to identify the right challenges and map the data necessary to create solutions inline with the problems to be solved or the challenges to be won.
It is no coincidence that the top 5companies in the world by brand value and turnover are all tech companies, as indicated in Forbes Magazine's annual report, The Most Valuable Brands 2020.
Why this premise?
Because the benefits that can be achieved by guiding the decision-making process with data are numerous and entail greater sustainability, in terms of efficiency and long-lasting and exponential growth. Not to mention more satisfied employees.
As you may have guessed, the global companies that have seen an above-average increase in turnover in recent years, all share a strategic data-driven approach.
This has led companies to understand the importance of enabling their employees to understand and interpret data. And above all, in deciphering how the data strategy evolves in the different phases of the user's journey and product life cycle.
Data Thinking arises from the combination of two disciplines, Design Thinking and Data Science, as a useful methodology to facilitate user-driven innovation processes.
It is a holistic approach to the systematic identification of use cases where data creates value and improves products and processes. Right up toforming the basis for new business models.
As anticipated at the beginning of this post, we have developed a Data Thinking training course for a well-known Italian group in the Fashion sector.
The ultimate goal is to identify a group of people who, once they have acquired the skills necessary to make the company evolve, return to their activities with greater knowledge and the ability to instill in their colleagues the right mentality to face the challenges ahead.
As in all the projects we carry out, the proposal involves various professional roles as stakeholders, who are invited to contribute along with their experience and their wealth of knowledge of the company.
First, the company selects participants through a pre-selection based on certain eligibility criteria or by invitation.Naturally, this selection may relate to the entire company or just a part of it.
The learning path that we envisioned consists of 3 phases:
In this first phase, which follows the pre-selection of candidates conducted by HR, the goal is to explain and teach the basics of Data Thinking and to select the group of people who will lead the contamination in the company.
Whether they are evangelists, ambassadors, or talents, their mission will be to spread the Data Mindset.
The involvement of candidates takes place through a playful (gamified) experience that begins with an invitation to take part in a game. The invitation has a predefined narrative style and theme that make the experience immediately immersive, colorful and interactive.
In the Data Awakening phase, there are workshops dedicated to understanding how to engage and train future talents through gamified experiences.
The format of this learning game is interactive and involves the sharing of various kinds of content - such as quizzes, live webinars, interactive videos - via the app, landing page, or other touchpoints.
At the end of each lesson or mission, the results are shown on a dashboard that monitors and reports the progress of the participants - giving each of them a score and rank.
At this point, the talent pool is officially formed. In this second phase lasting two weeks, the goal is to apply all the concepts assimilated in the previous phase to everyday working life.
In the Data Thinking phase, workshops are held that from time to time lead to the definition, planning, construction, testing and refinement of a data-based model for Digital Transformation. At the end of the design sprints, this model becomes areal prototype.
Thus begins the process thanks to which the group understands how to spread this model in each of their business units.
In the third and final phase of this process, the goal is to apply all the possible paths designed in the previous phases by the various business units to implement Data Thinking.
For this purpose, we use an iterative approach of retrospective and training on the job, which the team of consultants carries out together with the participants through the following steps:
They ask questions in a controlled environment through surveys and other real-time feedback solutions. They ponder what the right questions to ask are, who has the necessary information and where the crucial bits could be hiding.
The key is knowing the ultimate goal. Why is getting feedback so important? By having a clear goal, it will be easier to ask the right questions.
Once the right questions have been asked, data relating to the answers is acquired.
One needs to understand how to collect all the data and how best to group data sets to give them order and meaning.
In this step, with the information now acquired and organized, it is necessary to focus on the analysis. Data is only valuable if it can be used to guide operational decisions.
Through analysis, we reveal the power behind the acquired data. One must ask oneself: what does all this mean? Where can it be applied?How can I improve my business with all this data available?
Now, thanks to the data collected and analyzed, one must act to create experiences that their fellow employees will love. Also, the feedback gathered from employees can help to improve their satisfaction and retention.
In each phase from Data Awakening toData Weaving, the use of certain communication channels is envisaged, such as:
● Email for one-to-one communications with participants
● The Intranet for sharing knowledge and progress made during the learning process with the entire company
● Social media to connect with the community and document the project.
In this way, it will be possible to optimise the content produced and use them as a sounding board - both internal and external.
In conclusion, if your job in the company is to fill a skills gap and create a widespread data mindset and culture, this model could point you in the direction you want.
So, what do you think? How does your company work to build or nurture its corporate culture?