The challenges of “tidy” data

CONTEXT: My organization is an advertising agency (Publicis Canada), and my team (Nurun Toronto) is the division focused on providing digital consulting and professional services. Our clients are well-known, large-scale, national (Metro, Rogers, WestJet) and international brands (Coke, Merck, FCA, Sephora, Nestle, LG), as well as some mid-sized firms (Lennox, Kubota) and government entities (OLG, TTC, GO Transit, Metrolinx, Hydro Quebec, Canada Post, Purolator).

What challenges does your organization face in converting data it has collected into tidy, analysis-ready data?

One might expect a lack of technical knowledge to be the primary challenge in converting our abundant corporate data into “tidy, analysis-ready data”, however I posit that the greatest challenges are actually operational.

The first issue is centralization and ownership. Consider my division (~50 employees), the local office (~350 employees), the national company (~600 employees), the regional group (~35K employees) and the holding company (~80K employees). Within all of these groups, there are multiple systems in place, however there is no sole “owner” who is responsible for them.

Here are a few of the tools we use that could be insightful for the organization:

  • HRIS systems containing employee and role information
  • Survey tools such as SurveyMonkey to collect employee and client feedback
  • Web analytics tools (Google Analytics)
  • Communication tools such as Skype and Slack
  • Intranets (WordPress, Confluence)
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We also maintain systems data for some of our clients that house useful data, including CRM systems (Salesforce), marketing systems (Adobe Experience Manager) and analytics tools (Google 360, Omniture, etc.) Here again each system is managed by independent, siloed teams, and thus the challenge to gleaning any organization-wide benefit or insights would be one of centralization and ownership.

A second important challenge facing “tidy” data analysis is that one of security and privacy, both client/customer and personal/employee. Collecting and analysing data and transforming it into meaningful insights and recommendations for the organization requires access to sensitive and sometimes protected/restricted data.

In my opinion, our organization is currently not well-structured to ensure full adherence to all data privacy and security compliance requirements, and thus a concern would be that (a) data would be shared with those who shouldn’t have access, or (b) important data would be excluded from analysis due to inability to share for privacy reasons.

What tools, if any, does your organization use to aid in the process of tidying data?

As a provider of digital technology and consulting services to our clients, we have in-house Analytics team who specialize in the capture, processing, reporting, and analysis of web analytics data.

As a part of their mandate, they use common, industry-standard tools:

  • The “tidying” and processing of data is usually completed offline by our Analysts using Microsoft Excel.
  • Clickstream analysis is completed using the client’s chosen system, usually Google Analytics but also Adobe Analytics, Google 360, Omniture, Coremetrics, or another platform.
  • Reports are usually manually prepared with Excel (for graphs and tables) and compiled in PowerPoint or Keynote, and finally submitted to clients in a summary PDF format.
  • For “live” reporting and dashboards, the preferred tool is Tableau. Adoption of this tool is slow, however, as it requires a more training and knowledge both from our internal team as well as from the clients.

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