Even more interesting is that the process seems to be a long one: most respondents traced their Digital Transformation journey to at least five years, some also too much more extended periods.
I’ve mentioned this other times: one of the complexities with Digital Transformation is that we perceive it as going against a moving target. The reason is that we focus too much on the technology side of it. As technology constantly evolves, we see our efforts vanishing if confronted with the speed at which innovation runs. Five years ago, we barely talked about micro-service architecture. Today, we’re fully into a distributed blockchain.
Evolving Expectations are the Key to Digital Transformation
But technology adaptation alone is not digital transformation. However, a vital component of this transformation that we need to recognise is to build the organisational capability to adapt to new technologies.
The research identifies three key elements that impact businesses and organisations and influence the need and direction of this Digital Transformation.
Customer Expectations are evolving. Customers want frictionless end-to-end experiences with companies, even in the B2B setting. But they’re not necessarily willing to pay more for this, thanks to the availability of products across global marketplaces.
Employee Expectations are gaining ground. Employees have never been core to the transformation efforts of organisations. Decades of outsourcing, off-shoring and cost-cuttings have got us used to the fact that employees have often just been considered a “side-effect” to sacrifice on the altars of efficiency. Today things are different. Talent is scarce in many critical areas to digital transformation, and companies need to consider reskilling efforts for all employees. This gives employees a new bargaining power in their relationship with employers, as recently demonstrated from the increase in attrition numbers.
Society is changing expectations as well. For example, there is a renewed attention to the social responsibility of companies across multiple domains and the search for deeper meaning in work by younger generations.
As you see, none of these is about technology. It’s about expectations. Which drives to a significant focus that the researchers suggest. Digitally mature organisations can understand these expectations by using data and insights derived from data.
Developing a Data-Informed Culture
Thus developing a culture that is data-informed, not data-driven is a clear distinctive mark. But what does it mean (bold is mine)?
Digitally mature organizations embrace data […] and use it to make better, faster decisions. However, data informs, not determines, their decisions. Analytics are important, but judgment and critical thinking ultimately set the roadmap. All employees, not just the data scientists, use data to develop new insights and foresight instead of relying on past experience.
This translates into an immediate consideration: developing a data-informed culture is an act of intentionality. It means setting a clear priority for the entire organisation to become digital literate beyond an elected team of analysts. So how do you achieve this?
Step 1: Remove data ownership as a power or status criterion
The first step in resolving a cultural conundrum that deeply affects most organisations today and, as we have seen, is a negative deviation of the hierarchical model
. Data and information in most organisations today are highly segregated both horizontally
across functional silos and vertically
across layers in the bureaucratic pyramid.
Data like all information is Power, and not everyone will embrace this transition easily.
Access to Data is a sign of the importance of your functional expertise and the status associated with your level in the organisation. Both elements are, at the same time, cultural and organisational and need to be removed to make room for a new way of intending competency: not by owning the data but rather by using it.
Step 2: Don’t make Analytics and Elitist Endeavour.
The importance of Data and Analytics is not new. Many organisations have started to look into this arena some years back, and it’s not a mystery that Data Scientists are among the most sought roles on the job market. This is also because, once they recognise the need, most organisations have created a small team, high up in the hierarchy, in isolation, that could swim in their data-lakes in isolation from the business environment.
It’s easy to spot these organisations. The data scientists speak jargon that is not understandable by many. The sponsors (i.e. the top executives that created the Data and Analytics unit) constantly talk about their data-driven strategy. Board meetings have long sessions on data that are difficult to understand. Yet the impression is to see one of those medieval kingdoms in Europe where a late Alchemist influenced the courts with the tales of their experiments.
This moves us to the second step: you need to move away from this elitist view
of analytics. Although it is senseful to build a data organisation
and build specialist competencies around data engineering, it is vital not to restrict the entire data strategy to just a limited number of omniscient.
Step 3: Make data Available and Simple.
The third step starts from considering that if Data is the new oil
, it needs to be widely available
in the organisation. Functional barriers need to be lifted. Knowledge about Data needs to be expanded across all
employees to access data when they need to make a decision.
This means thinking about the accessibility of data and the simplicity of the concepts behind it. Careful: this does not mean that we ask each individual to develop their own analytics. This is another relic of the past: as many organisations built their last technological transformations around different ERP versions, most teams set their own analytical skills. This is because reporting was seen as a mere transactional focus. Data access was also technically challenging, which led to the proliferation of Excel as a management tool, with every department running its little dashboard and its little empire of segregated knowledge.
That’s why I think simplicity is the key. Modern data access tools are all about visualisation and decision-making support. With the proper upskilling, all workers can easily access data and use it in their daily activities.
Step 4: Ensure Trust
The last and most vital step to achieving a Data-Informed culture is that people in your organisation Trust the Data.
I’ve seen it many times. You present a new project idea, a new product, a new service. You have data to support it. Somebody in the room, often a manager of another department, challenges you not on the idea but the data. This usually happens with HR, as it’s a profession not seen as capable of dealing with numbers
Building trust around the Data
means addressing all the three steps above at the cultural level. Removing information-linked status often means removing the idea that a specific set of Data is associated with a source that ensures its quality through ownership. Thus you need to move to a culture where Data is owned collectively
and every person feels responsible for data quality. The garbage-in garbage-out
issues become a problem that every employee is willing to tackle.
Removing the elitist view means that employees need to be equipped with new skills to understand data and aggregated information. We have seen with the recent pandemic how difficult it has been for people to cope with basic statistic concepts
such as exponential growth. Data Literacy needs to be built through learning, exposure and constant nurturing of the tools to enable these new competencies.
Finally, Availability and Simplicity call for a more substantial consideration of the autonomy of employees to work with data. Let me give an example. Many organisations restrict access to Data based on data protection, privacy or data-security considerations. Locking data away, however, is not the solution. Instead, you need to train people on how to use data securely. Moving from control to autonomy is a culture change that is not to be underestimated and is at the core of the self-management efforts that many organisations are doing at the heart of their transformations.
Becoming a Deliberately Data-Informed Organisation
The above steps make it easy to understand that the journey to Digital Transformation is not about technology. It’s about profoundly restructuring the fabric itself of your Organisational Model
and making it coherent with a new Business Model
where Data is pivotal, a new Operating Model
where data informs each step of your Value-Chain, a Strategy
where data tells every decision step, which calls for a Leadership that works with data, and a Corporate Culture
that is built around renewed concepts of Autonomy
Being a Data-Informed Organisation means nurturing all levels of your organisation with Data that can Trusted and the Autonomy to decide when and how to use this Data.
Are you ready to start this journey? If so, then you are prepared to achieve your Digital Transformation.
What do you think?
Here below are the links to the two articles already issued. A third is underway.