By Anne Milley
By Anne Milley
One of the biggest mistakes organizations make that prevent an analytic culture from taking hold is not investing in ongoing education/training. Early in my career at a large retailer, I asked to take a SAS class that I would pay for myself. I’ll never forget the response to my request: “Well, we can’t afford to let you take the time.” So, I learned from the software manuals what I needed to know, but could probably have learned a lot more a lot faster in a structured hands-on class. When an organization pays (with time and/or money) for an employee’s training it sends a signal that the organization values that employee. It shows that the employer wants to invest in sharpening the employee’s mind so that they can be prepared to better solve new problems that come their way.
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People who earned their graduate degrees in statistics (or other quantitative disciplines) a few decades ago likely didn’t have a lot of exposure to newer methods like neural networks or definitive screening designs. When people aren’t exposed to the advantages of new methods and how to apply them, they tend to stay with what they know. Their organizations miss out on the benefits they could be realizing, and they will likely experience more competitive squeeze from organizations that invest in continuous learning.
We see successful organizations providing a variety of ways to keep current:
- They have “Analytics Days” where analysts convene to hear guest speakers, learn from colleagues about the success or failure of recent projects, and attend workshops on relevant topics.
- They enable employees to take professional courses or bring those courses on site (courses like those offered by SAS Education) and often have their own training department.
- They support attendance at conferences so workers can gain exposure to new ideas and applications.
- They permit employees to join and participate in professional organizations like the American Statistical Association or INFORMS in the US, and others like the Royal Statistical Society in the UK. (Note: people are organizing to meet more frequently locally with a growing number of Predictive Analytics Meetup groups — great to see how international these have become).
- They may have programs that allow workers to be assigned temporarily to another group or office to experience a different part of the business.
- They pay for courses at universities.
- They provide flexible work schedules so employees can manage their time such that they can attend classes or take advantage of online learning libraries, instructional YouTube videos, and free online learning from the likes of Coursera and Udacity.
Think of training as analogous to adding more organic matter to your soil — you are maintaining a healthy growing medium to have a sustainable harvest. Similarly, when you invest in training people, that learning gets plowed back in to your organization so you can sustain value creation.
Another good sign of a healthy analytic culture is well-equipped analytic workbenches with an appropriate infrastructure to enable productive analysis, where the analytical flow has minimal interruptions due to over-burdened networks, underpowered hardware, insufficient memory or poorly designed software. If the main analytic workhorse in an organization is a spreadsheet, that typically signifies a low value on doing quality data analysis.
Organizations with strong analytic cultures have powerful analytic infrastructures with multiple usage paradigms — coding, visual discovery, wizard-driven (for the mundane tasks), in-database and more. Of these, I’d like to focus specifically on the benefits of interactive and dynamic visual discovery tools. These tools let you:
- Realize faster discovery. You should be able to answer questions about your data as fast as you can think of them and find the stories in your data.
- Achieve easier collaboration. We are highly visual, and when the data are brought to life through interactive graphs, we process it faster and can contribute faster.
- Provide compelling presentation of results, making the invisible visible. You can showcase the data’s story in “data movies,” making the story more accessible to everyone, not to mention more memorable than a static report or presentation.
Finally, evolving and maintaining an analytic culture is a long-term commitment. If you have soil of unknown quality it would be in your best interest and the best interest of your crops to get it tested. Similarly for organizations, Tom Davenport and others have developed assessments to see where organizations are analytically on dimensions like people, process, technology and most importantly, culture. If you elect to have a consultant be a part of the assessment, the outside perspective is often a good catalyst to move things forward. Once you’ve taken the next step to show you value analytics, keep going!
To inspire your thinking, here is a great example of a long-term approach to effect a better analytical culture. The United Kingdom is two years into a 10-year campaign mounted by the Royal Statistical Society: getstats. They are campaigning for a cultural change because they recognize the benefits of a statistically literate society at work and at play — fit citizens and productive employees make better decisions that more optimally allocate resources.
Here’s to a more analytically rich culture–especially in this first-ever International Year of Statistics! I encourage you to invest in your people, create dynamic and well-equipped workspaces, and provide your analysts with a powerful analytic infrastructure to help them flourish. Successful, confident employees are the root of successful organizations, so nurture them!
Note: A version of this post first appeared in the International Institute for Analytics blog.