By now, you’ll probably have read all about the benefits of becoming a data-driven organisation.
There’s no need to go through them again. What is crucial, as you begin to increase the data maturity of your business, is installing the right people in the right roles to ensure ongoing success with your data and analytics strategy.
Analytics-driven organisations continually develop their people, process, data, strategy and technology to achieve their commercial objectives and KPIs. This article will highlight some of the key roles you must have if your organisation is to become truly data mature.
You can start by building a centre of excellence within the business. Some of the key roles/categories of employment to consider when doing this are as follows:
As any successful data and analytics approach must be driven into the organisation’s DNA from the top-down, start by thinking about how to shape your leadership team to reflect this. A Chief Data Officer can be responsible for the overall data strategy, and the ROI of analytics. They can also assign data custodians or stewards for each department (e.g., the HR Director owning HR Data, and the Finance Director owning finance data, and so on).
In a report published in April 2020, C-suite respondents to a Gartner survey reported that organisational culture and lack of data literacy were two of the biggest roadblocks to success in data and analytics. Buy-in from senior figures within the business is the most critical start point in building a data literate culture, as it will then cascade down through departmental managers to employees on the front line of operations.
You’ll need some figures who’re responsible for integrating the tools and technology needed to run data and analytics as well, such as a Data Engineer. A Data Engineer will form part of the tech team and be responsible for the implementation of workflows. As part of the broader analytics team, data engineers are responsible for the data pipelines and the orchestration of data set including those from data science teams.
Integration of modern technologies is set to be a key facet of business going forward.
Gartner estimates that ‘through 2023, data scientists and analysts will lose 60 to 70% of their productive time to activities like finding, preparing, integrating and sharing datasets, making data engineers a must-have persona in their teams‘.What Are the Must-Have Roles for Data and Analytics? Gartner, 2020
However, Gartner’s study goes on to confirm that, as organisations move up the data maturity curve, and AI/machine learning begins to automate more data science processes, the need for extra ‘hands on deck’ will be reduced.
It is obvious that you’ll need to think about who handles the analytics functions within your teams. Data analysts are responsible for the collection and interpretation of data. They’ll report results back to relevant members of the organisation and will need to be able to analyse and find patterns and trends within datasets. It’s important that they work alongside others within the business to keep analytics aligned to business needs.
Analysts can also take charge of data visualisation. In essence, data visualisation is about how the data and resulting insights are presented in pictorial or graph form. Good data visualisation is important because it ensures that the ‘story’ of the data is told in a way that is easily digestible and, ultimately, actionable. Good visualisation tells a story, highlighting key information and making insights accessible.
Another significant role is that of the data scientist. A data scientist’s job is to analyse data for insights, collecting large sets of structured and unstructured data and cleaning and validating the data to ensure accuracy, completeness, and uniformity.
When tools and technologies are in place, you’ll need a Delivery or Change Manager in place to guide specific data and analytics projects in different teams across the business. They’ll be responsible for the orchestration and success of all projects within your data and analytics portfolio, planning, executing and delivering all projects on time, in budget, and within scope, aligned with business objectives. A Delivery Manager will also take care of the vital process of tracking project status throughout the lifecycle, managing and reporting on teams as they carry out requests.
The Change Manager will play a slightly more strategic role in developing strategies to ensure successful outcomes against business objectives, as well as driving data and analytics adoption into the culture of the organisation. As we mentioned earlier, they will need the support of senior business leaders – like the CDO or CEO – and be empowered to build data literacy by establishing tools to develop people, skills and processes.
For smaller organisations, who may be unable to immediately develop or improve their talent pools, some of these figures can wear many hats, taking on additional responsibilities until the organisation is ready to add new talent. If this is the case for your organisation you can start by repurposing transferable skills and building the infrastructural and governance models that’ll help your existing data & analytics teams to thrive within a set of best practices.
Gartner also suggests making use of working with external data and analytics service providers, who can temporarily support your digital journey by filling role deficits or supplying training and upskilling to augment your existing resources.
As you begin to graduate up the data maturity curve, you’ll then be able to give more consideration to adding these specific roles into your internal organisational structure and revise governance around handling of processes.
As the Gartner report notes, the growing significance of data and analytics to business strategy and process is presenting businesses with an imperative to rethink roles within their organisation.1 While some traditional IT roles are being disrupted by ‘citizen’ roles performed by nontechnical business users, there are also new hybrid roles that cut across different departments and functions, blending technical ability with business acumen.
For SMBs looking to become truly data-driven, it’s vital not to ignore the definition of these roles, and begin to think about how you can introduce these roles and categories of work into the wider business structure.
This article is part of our Data-Driven SMB series. For more information, advice and resources on how to accelerate your organisation’s data and analytics maturity, click here or contact us today.
Max has a background in Business Intelligence, Analytics and Data Warehousing with over 12 years in the field. He leads the delivery of enterprise level Analytics projects with a mix of technical and consulting elements at Truecue. He has been working across a multitude of industries and strives to get business value and insight out of each project, he enjoys the challenge of solving data problems with the intention of delighting our customers.