Surfing the Data Wave: How to Master the Change to a Data Culture
by Till Achinger
Some Comms teams are drowning in data yet still starving for insights because data has not been actively incorporated into decision-making and translated into action. By Till Achinger.
Rather late, but fiercely, Communications is caught up in the data wave. Those who don’t bring data are no longer heard by management and the external environment has never been so complex and dynamic. Only Communications has the tools to manage the complex relationships that make the difference between success and failure in the stakeholder economy. It can greatly increase its relevance, but only if it can master this increased complexity and demonstrate its contribution with the help of data. Communicators are faced with the decision of surfing the data wave or letting themselves be swept along by it.
The data and tools are all there. Some Comms teams are already drowning in data and still starving for insights. This is because data must be actively incorporated into decision-making and translated into action. Data can’t be just bolted on; it means changing the organization. And to support this change, trust in data must first grow and its use must become a given.
Without a supportive data culture, insights will be discarded, tools will go unused, and training will not be taken advantage of. However, if the cultural change succeeds, the processes and capabilities will follow almost by themselves.
The following fictitious example is composed of the approaches that have proven successful in our consulting work. No matter the team size, these small, concrete steps in four phases help overcome “decision paralysis,” minimize planning errors and give culture a chance to keep pace.
Phase 1: Explore
Goal: Communications executives have decided where they want to focus their data resources.
Head of Comms Martina knows that for the transformation to be “data driven”, she will need a change agent first and foremost, and only secondarily a data analyst. She is handing the task over to a Media Relations associate, Jane. She has practical experience in Communications and can make herself heard by her colleagues. She still has to acquire the analytical skills but is motivated to do so. Even more so because a new key position is being created here.
Jane uses offerings from her PR industry association to get insider perspectives from companies who are further along and connect with peers facing the same challenges. She takes an online course on the basics of analytics in Communications. In parallel, she takes stock: what data and tools do we have (media analysis, social listening, social media accounts)? Which ones can we get access to with little effort and cost (web analytics and intranet usage from IT, employee survey from HR)?
Jane shares the information and impressions she has gathered with the Communications function’s steering committee. They discuss what role data could play in the further development and implementation of their strategy and agree on the pilot projects in which data could have the greatest impact. It’s okay if the goals are vague at first. Over time, the insights gained will help to make them more precise.
Phase 2: Build
Goal: The benefits of data-based communication have been practically demonstrated and employees in various disciplines have had positive experiences with data-based processes.
One by one, Jane implements several pilot projects, always taking an interdisciplinary approach. As a sparring partner, she works with her internal ‘clients’ to first identify the critical decision points and then find the data to facilitate the decision and measure success. Sometimes a single metric, such as clicks on a post or registrations for an event, is enough. By focusing on specific projects, Jane avoids the typical pitfall for data specialists of becoming a sort of general research department.
At least in the beginning, Jane will need help setting up the tools and sparring with analyses. Sometimes specialists from Marketing or IT can provide support. Otherwise, there is always the option of relying on external consulting. Here, you just have to make sure that they can transition between strategy and ‘hands-on’ and know-how is actually transferred. It becomes easier to obtain budget for this the greater the perceived benefit of the data projects for the entire company.
Jane is therefore looking for solutions to the company’s key challenges. Using social media data, employer review platforms and surveys, she finds out that the company is not addressing issues that are of great importance to urgently sought professionals. She also identifies platforms and influencers through which to reach them efficiently. With the help of a clear forecast of the targeted results, Communications can bring in additional budget for a campaign. During its execution, Jane continuously measures which actions and content have the greatest impact to ensure resources are used efficiently. For the project, she brings together data from media analysis, social media, the company website and HR software. She first copies them by hand into an Excel spreadsheet.
In the example above, Jane first exploratively seeks new insights for the strategy, and later measures operational results for improving implementation. Both approaches form a control loop. Where you start this depends on capabilities and current needs. The important thing is always to enable better decisions rather than just looking in the rearview mirror.
Phase 3: Integrate
Goal: Continuously available data offerings create lasting value for Communications and regular touch points with data for many employees.
Based on the pilot projects, Jane develops solutions for specific, crucial and regular use cases in the form of dashboards, reports or alerts containing only the relevant information. She sets up a business intelligence tool such as Tableau or Power BI as an ‘Insights Hub’ and automatically brings together the data from the various sources in it. She no longer needs the Excel spreadsheet.
This results in a report to prepare for the morning session, a dashboard to develop new topics, and alerts for critical social media posts. At key meetings, Jane is always there to bring insights from the analysis into the planning process and to catch unanswered questions. Instead of reciting numbers, she tells a story about what they mean. Even in her absence, the Communications leadership team turns to the Insights Hub and makes data the new norm. Discussions become more factual when you base them on data.
For some applications, data sources are still missing, such as a regular survey on the company’s reputation. To systematically identify and close gaps, Jane is guided by tried-and-tested frameworks: the Barcelona Principles and the ‘DPRG/ICV Levels of Impact and Evaluation of Communication’. Some applications require complex methods and tools such as network analysis and natural language processing. The successful pilot projects help to obtain budget and to increase the team, not with a data science unicorn but with a smart graduate who has useful analytics skills from Empirical Social Research and an enthusiasm for communication.
Phase 4: Scale
Goal: All Communications employees are empowered to independently access new insights based on data, make decisions, and evaluate results.
The collaboration with Jane and the use of the Insights Hub have sparked a desire in some team members to search for new ideas and answers in the data themselves. For this kind of data democratization, the data must be accessible to everyone and maintained in such a way that it can be relied upon without question. Above all, users must be able to deal with them.
Jane records e-learning videos explaining key metrics and answering frequently asked questions. She also shares external links to beginner courses for analytics and data storytelling, many of which are out there for free. The videos are available when they are needed. In a Teams channel, all users can help each other and share practical examples. Jane helps where the community can’t.
Not all communications professionals want to become data analysts, nor will they. That would not be efficient either. What makes sense is a hybrid model in which everyone receives basic training in the use of data, while data specialists expand the offering, can be called in as internal consultants, and proactively approach other team members with new insights.
Begin
There is no shortage of tech and data but a shortage of processes and culture. The first steps don’t even have to cost a lot of money. So there’s no reason not to start implementing them right away. Knowledge and experience are only gained through application. If this experience is consistently positive, the cultural change will also succeed.
No one has ever become a surfing world champion by reading guidebooks about it. Go throw yourself into the waves!
Source: IPRA
