The 4 Pillars of an Analytics Health Check

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Whether you're starting from scratch or looking to evaluate an existing analytics practice it's important that you review the resources allocated to and output of analytics within your organization on a regular basis. 

I've come across many cases where a client has invested in data and analytics but for one reason or another they end up being heavy on reporting but light on actual insight. Indeed, scoping analytics can be a challenge, particularly because unlike other marketing functions which typically produce a tangible output (e.g. a web build for technology, mock ups for creative, a wireframe for UX, etc), analytics practitioners are faced with the task of delivering something that is very much intangible, that is, insight. Of course, insight needs a vehicle and most often it's delivered through tables, charts and data visualization nested within a PowerPoint deck or an Excel dashboard. The problem is most of the time we end of focusing on the means (the report) rather than the ends (actionable insight).

I believe that reporting should be as lean as possible, which means you should aim to get as much value out of your data in a timeframe that matches your capacity to actually take action. That's not to say you should rush your analysts, or that you should allocate fewer resources to reporting. Rather, you should seek to find the right balance between reporting and analysis without over delivering on the output (i.e. PowerPoint decks or Excel sheets). 

Measuring the impact of your analytics practice is another story, which I covered here. For now, I want to talk about evaluating the health of an analytics practice. Conducting an analytics health check is something you can (and should) do regularly, the goal of which should be to assess whether you have a reporting structure in place that delivers actionable insight while also minimizing the effort needed to collect, analyse and produce reports.

When conducting such an audit there are four core components of your anlaytics practice you should examine, which include; identifying your report objectives, mapping your reporting audience and their needs, determining the frequency at which you need data and in which medium your audience want to consume the data. 

 

   

 

 

1 - Report Objective

This involves thinking about the objective, or purpose of each report that is sent out within your organization. For example, high frequency reports, such as daily and weekly reports are typically designed to provide a snapshot of performance as there isn't usually enough time (or data) for an analyst to conduct deep dive analysis. On the other hand, low frequency reports (e.g. monthly, quarterly, annual, etc) usually allow you to dig deeper into the data enabling you to provide much more meaningful insight and recommendations. Also, I generally find that when I’m working on low frequency reports (e.g. quarterly), these are typically designed to inform higher level issues, such as a business strategy (e.g. am I allocating the right budget to social media) as opposed to something more tactical (e.g. is my call to action or creative asset effective). 

Tip for Success

If you're evaluating an existing analytics practice, conduct an audit of all the reports that are sent out within your organization and try to determine the purpose of each report. This may not always be clear, so it can be helpful to conduct a survey among the reporting audience and ask them why they want to see this data and how they use it. 

2 - Audience

Considering the audience, or stakeholders, of your reports is essential yet often overlooked. For example, are you developing reports that go upstream to C-suites and the executive branch, or are they going downstream to functional teams like creative or technology? Upstream reports tend to be more concise as C-suites usually want to see only the key insights and recommendations. On the other hand, reports that go downstream are often much more detailed and verbose. 

You will also want to consider other factors such as the business function of the audience (e.g. is the report going to PR, marketing, commerce, finance, etc) as well as the comfort, or competency level of the core audience when it comes to data. The latter is important as some individuals might prefer to consume data in more visual format (e.g. charts and visualization) while others might prefer to see data in less visual ways (e.g. tables). 

Tip for Success

Try to identify all of the stakeholders (and their business function) who currently receive reports, but also use this as an opportunity to identify new stakeholders who aren't receiving data but who may benefit from it. Also, consider different tiers of stakeholders, such as primary reporting stakeholders who actually action on the data vs secondary reporting stakeholders who simply need to be informed of performance.

3 - Frequency

This involves asking yourself (and your reporting audience) how frequently they need the data. The answer to this question is usually best answered by asking how often you will actually be able to take action on the data. If you don’t have the capacity to act on your data every day, then maybe you don’t actually need that daily report. On the other hand, if you have the resources to act more frequently and feel as though your not getting access to your data quick enough then maybe you need to move toward a higher frequency.The point is, try to find the right cadence of exposure to your data by ensuring you’re not getting overloaded with data you never use or stifled by data you’re not getting frequently enough.

Tip for Success

When you consider the reporting frequency that is best for you, think about both the report objective(s) and the types of actions you and your audience might take upon receiving the report. Our natural inclination is to request as many reports as possible, but if you don't plan on taking action on a daily or weekly basis then don't send out daily or weekly reports. On the other hand, don't wait too long for data if you have the capacity to act quickly.  

4 - Medium

This may seem like you’re overthinking it, but considering which medium and format your reports are delivered in can have a huge impact on how valuable they are to your audience.  Powerpoint is good medium for telling a story (reporting to C-suites on what you've achieved) but is limited in terms of what you can automate. Excel is a great platform for high frequency reports, and ensures the data is portable. It also allows you to automate laborious processes and provides a certain degree of freedom in terms of integrating other data sources. If you work with a wide range of disparate data sources (e.g. website, social media, CRM, EDM, paid media, etc) and you require data at a high frequency then you might want to consider an integration and visualization platform like Tableau, Qlik or Roambi. All of these mediums have different benefits and trade-offs, and you should weight these before deciding which is best for your needs.

Tip for Success

When deciding on which medium is best for you, consider both the report objective and desired frequency first. High frequency reporting across multiple datasets usually means you need to consider an integration platform like Tableau. But be wary as this can get expensive quickly, both in the cost of the build and the ongoing support/maintenance fees. Also, as a general rule I tend to advise that you stay away from reports produced in Word or rendered formats like PDF. It's fine to send a PDF along with an editable format like PPT or XLS. However, data wants to be free and when you send it exclusively in a rendered format the audience has no way to filter or easily refurbish the data in another format.  

Key Takeaway

Evaluating the health of an analytics practice isn’t something you do once and forget about. Requirements change all the time as your organizations digital strategy evolves and people within your organization come and go. Therefore, I recommend evaluating the four pillars covered above at least once a year to ensure your getting as much value out of your analytics as possible. Remember, the goal is the find the right balance between exposure to your data (i.e. reporting) and decision making, so make sure you find a solution that ensures you deliver the right data to the right people in the right format and at the right time.