Data Values
Change the data culture and landscape
Culture
Change
Processes
Trust
Why data culture matters
Organisational culture can accelerate the application of analytics, amplify its power, and steer companies away from risky outcomes. This section covers some of the key principles that underpin a healthy data culture.
Committing to a healthy data culture is forever
The development of a data culture is a continuous process. Commitment is required from all industry stakeholders if this vital transformation to succeed. The uninterrupted connection between all decision-makers and stakeholders in charge of data systems and processes is of paramount importance as they work closely towards a common goal.
The democratisation of data
It is difficult to impose change if people do not understand the concept; they have to see how it will improve the way they work. Decision-makers need to understand that taking the time to show their teams the benefits of data can actually accelerate the change.
The main takeaway is, get data in front of people and they get excited. But building cool experiments or imposing tools top-down doesn’t cut it. To create a competitive advantage, stimulate demand for data from the grassroots.
“Ultimately, everyone in the organisation has to adopt a mindset of data culture, but it doesn’t happen overnight. Creating a cross-cutting data set across the organization is a key for success.”
“Defining roles is an important first step in sourcing and integrating the right talent for your data culture. Business skills Technology skills Analytics skills Delivery managers Business”
Finding data-driven talent and workforce
In the end, everything comes down to finding the right people to implement change. The construction industry has a unique opportunity to attract young, ambitious talent with a data background. This talent boost could help accelerate change and facilitate the introduction, development and implementation of a healthy data culture.
The competition for data talent is unrelenting. But there’s another element at play: integrating the right talent for your data culture. That calls for striking the appropriate balance for your institution between injecting new employees and transforming existing ones. Take a broader view in sourcing and a sharper look at the skills your data team requires.
Identify Red Flags
Analytics capabilities are isolated from the business, resulting in an ineffective analytics organisational structure. Organisations with successful analytics initiatives embed analytics capabilities into their core businesses. Those organisations struggling to create value through analytics tend to develop analytics capabilities in isolation, either centralised and far removed from the business or in sporadic pockets of poorly coordinated silos. Neither organizational model is effective.
Over centralisation creates bottlenecks and leads to a lack of business buy-in. And decentralisation brings with it the risk of different data models that don’t connect. A definite red flag that the current organizational model is not working is the complaint from a data scientist that their work has little or no impact and that the business keeps doing what it has been doing.
“When people begin to believe in the data, it’s a game-changer: They begin to change their behaviours, based on a new understanding of all the richness trapped beneath the surface of our systems and processes.”
Conclusion
The power of habit and problematic contractual relations are two of the main obstacles the industry needs to overcome if it is to create a healthy data culture. The connection of analytics with existing systems and processes is a complex process that demands continuous commitment and the inclusion of all industry stakeholders. By outsourcing HyperCentral data specialists help drive that culture and ever-changing data landscape.
Please speak to an account manager and let us help you on your data transformation journey.