Introduction to PRISM: Reporting
In my last blog, I discussed the role of company culture in the development of a durable analytics strategy, and how building and nurturing that culture helps establish trust and engagement. These are all vital steps in helping to establish a decision culture which is driven by analytics and insight.
I’ve mentioned the 5 dimensions that we use within our PRISM methodology to help shape and define how our clients can build an effective roadmap for analytics – today I will focus on reporting, the second of the 5 dimensions within PRISM.
Reporting is the most obvious external artefact or deliverable from any analytics initiative. I’ve seen many organisations fall at the final hurdle by spending time to establish the right data ecosystem for analytics, spending time developing metrics that resonate with stakeholders across the business and reflect business needs, but then fail to execute on delivery and communication. Ultimately, an effective reporting strategy is a core part of an analytics strategy and should not be seen as an afterthought.
There are some common challenges that we often hear when clients talk about lack of reporting effectiveness. These can include the following:
• Too many reports that either provide contradictory or confusing insights
• Too few reports – creating a vacuum in terms of insight delivery
• Complex, hard to read reporting which turns people off
• Reporting that provides numbers, tables and charts but does not give a sense of what to do next
• Reports that are not trusted or believed and are hence under-utilised
So then, when investing in building up analytics capability it’s vital that companies address the needs of end-users. Again, service design for analytics is useful to consider, just as it is for understanding how to develop and promote positive cultural traits.
Some important considerations include:
• What reporting do people across the business need and how frequently?
• What decisions are likely to be informed through effective reporting?
• How do end users want to engage with analytics – what types of reporting?
A common challenge in marketing is the notion of delivering ‘the right message to the right person at the right time”. To achieve this requires a significant undertaking across marketing automation and effectiveness, building the right systems that can reach the relevant audiences with a message that is context-specific and that can be delivered at the right point in the customer journey to support the user engagement.
For reporting within the context of an analytics strategy, it is important to think along similar lines – it’s about getting accurate and timely information across to stakeholders in the business so they can include those insights in their workflow to support effective decision-making. Again, like culture, it’s changing a data culture into a decision culture. As described above, the strategies to get that insight delivered effectively with just the right level of information is no simple task. So, let’s break this down into some key components for success.
Depending on the type of report, automation can and should play a pivotal role in delivery. Processes and workflows that support automation can remove manual steps, removing the chance for human error and allowing report creators the time to focus on more value-add activities such as analysis, while saving costs. These processes also offer audit opportunities to support compliance objectives, for example.
Impact & Value
It’s vital, of course, that reports / dashboard / infographics all play some role in the decision-making process. Stepping back to evaluate the value from reports, and what assumptions they support or challenge is key to ensuring that reporting strategy positively impacts analytics. (We’ll talk more on how we ensure that impact and value are embedded into analytics reporting through a measurement framework in a future blog!)
It is common to hear that we are constantly collecting, processing and transforming ever increasing amounts of data. For the typical end-user in an organisation, the amount of data they have to make sense of only increases over time. Breaking through the noise, providing a clear message through reporting, insight becomes a key differentiator in delivering reporting that engages people, that supports intuitive understanding in a way that is sharable across the business. Telling a story through data is a complex skill, combining many skillsets not least from careful consideration of effective visual analysis. Again, focusing on the needs of the end-user as a key stakeholder in the service design of analytics will help you to understand the right visualisations to use – audience and purpose are key!
In our next installment, we will be focusing on the lifeblood of analytics – data, and how to support effective data processes and governance within an analytics strategy.