Getting Started with Analytics.

1. Getting Started With Analytics
This thought piece provides an overview of considerations for an organization which is getting started
in analytics. Given the potential availability of multiple sources of data from different functions of an
organization, it is important to take a holistic approach when planning these initiatives.
1) Sometimes more is better: The more sources of data you use in your analytics, the more robust
a picture you can paint for your organization. Employee surveys typically touch on multiple
topics; however, all of this is based on employee opinion. Tying this opinion to actual employee
behavior or business performance (e.g. at the group or location level) can help shed additional
insight into how your human capital investments are impacting the business.
2) Put time on your side: Relationships between what employees think and feel have an impact
on what they do, and what they do ultimately impacts the business. All of this, however, takes
time. The more time you can incorporate into your analytic approaches, the better your ability
to detect these relationships.
3) Start with a conceptual model or framework: Analytics start with the questions that matter
and a framework based on knowledge of the business and organizational sciences that guide
the data analysis. However, you want to consider alternative hypotheses for why the data are
coming out the way they are. This is where looking at multiple sources of data over time can
play a role in ruling out other explanations for the insights you are finding.
4) Determine your focus: Analytics mean many different things ranging from simple dashboard
and benchmarks, to indicators of the impact of an activity or program, to segmenting groups of
employees/customers, to predictive modeling. Each focus requires different resources,
strategies, and timeframes. Determine the focus early and you will get the data you need.
5) Focus on metrics that matter, not just the metrics you have: Use the metrics that have a clear
link to the way your organization measures success and creates value. If these don’t exist now,
there may be a bit of work ahead of you to articulate what these measures are and find a way
to either measure them directly or through a proxy measurement.
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© 2012 Critical Metrics, LLC
Seattle, WA 98101
www.critical-metrics.com
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2. 6) Start small: Find one or two small projects that can be completed in a short amount of time,
with a small amount of resources, and with a low risk of failure that will potentially generate 1-
2 analytics champions in the organization. After that, focus on areas that are pain points in the
organizations; analytics that help alleviate pain are ones that generate buy in and support. The
key is not to overpromise what analytics can do.
7) Build partnerships with data owners: Truly insightful and useful analytics draw on data from
multiple sources within an organization. Often needed data may reside in finance or marketing.
Forming alliances and building projects that benefit multiple stakeholders (e.g., identifying
human capital drivers of customer satisfaction) are likely to garner needed support and
resources.
Please contact us for permission to re-print or re-distribute this article.
© 2012 Critical Metrics, LLC
Seattle, WA 98101
www.critical-metrics.com
Page 2 of 2