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Part 1 :
The video: https://youtu.be/l6ISTjupi5g
Strata Jumpstart: Kathryn Dekas, “People Analytics: Using Data to Drive HR Strategy and Action”
Directions:
Submit a PDF document that provides answers to the three questions posed at the beginning (and again at the end) of the video.
Include both the questions and your answer to each of these questions. It is okay to include a bulleted list within your answer, but this list must be included within the context of a paragraph written in narrative form. Use single-spaced paragraphs, full sentences and write in your own words.
This class is about communicating information. Be sure your submission communicates each question and respective answer clearly and concisely. The questions can remain posed as questions, or you can turn them into section titles. Your reader should be able to scan over the document and get a clear sense of its content and order. This can be done with text formatting and alignment.
Part 2:
Post a new discussion that includes:
#1) A full paragraph (or two) that makes a concrete connection between the information presented in the People Analytics video and the information presented in the Davenport et al. article linked to above.
For example, one option would be describe how Google’s work in this area illustrates a concept presented in the article.
#2) Provide your own ‘response’ to this week’s materials in a complete paragraph.
For example, you can simply reflect on the video content (what was interesting, what was surprising), discuss the class readings or the content in the video ‘lecture’ posted this week. Note: While the topics of the Google studies are interesting, try to focus this discussion on research/methodology/tools.
Respond to two posts:
Responses should acknowledge the points made in the original post, then should add to the comments in a meaningful way. It is okay if your responses include points you made in your original answer.
POST 1:
#1) A full paragraph (or two) that makes a concrete connection between the information presented in the People Analytics video and the information presented in the Davenport et al. article linked to above.
Both the book and the video draw the conclusion that analytics are the way that businesses get better. Although the video does focus only on Google’s approach, the book dives more into other companies that have begun adapting the use of analytics. Both the book and video discuss how the strength of analytics comes, not from the ability to gather data, but the ability to apply the data. As outlined in the book, sometimes the best approach to “embarking on the analytical journey” is to find a problem you’re looking to solve.
This idea of problem-solving with data is something that the video really discusses too. The examples given in the video, such as how the company was able to squash rumors that were going around, really speaks to the power of analytical data. I’m certain we’ve all had jobs where we would get disgruntled because of rumors that would circulate. These rumors can make us feel like the company is playing against us at times. I think for a company like Google, that wants to be seen as very employee-friendly, it’s important that they take these steps to stomp out rumors that might discourage their employees. If more companies were able to apply analytical data, there is no doubt to me that more companies would be able to retain employees, or increase overall satisfaction.
#2) Provide your own ‘response’ to this week’s materials in a complete paragraph.
What was really surprising to me was how impactful Google really made analytics feel. As I discussed a bit above, the idea that Google was able to dispel overall negativity in their employee base by simply responding to circulating rumors is impressive. But the fact that they were able to counter those claims with hardened data, that employees couldn’t refute, is even more interesting. I’ve worked for companies where employees feel really negative about their job, and it’s because they all spread rumors around about how unfair everything is. I always assumed that the lack of any word from managers was more-or-less their safe HR-approved approach. So, when Google not only acknowledged those rumors, but also asked for more to test, I was really stunned. To me, that shows that the company has some integrity, and isn’t afraid to tackle employee problems head-on. That’s not something a lot of companies would do.
POST 2:
It’s becoming painstakingly clear that analytics has become one of the most important aspects of business regardless of the department or industry. Whether its personnel analytics, supply chain management, or analyzing customer satisfaction, analytics are indispensable everywhere. The first step in implementing any new analytics project is to determine what the problem is. The Davenport, Harris, & Morison (2010) paper described this step as the company developing an initial goal to work towards. One of Googles examples was to determine the opinion or myth they were trying to analyze. Without a concrete goal or problem to solve the data collected won’t be as beneficial to the decision-making process.
The Google personnel analytics video outlined a simple analytic value chain demonstrating a step by step process to collecting, analyzing, utilizing data for analytics. The Davenport et. al. (2010) article also explained how this was this chain was essential to any organization using analytics. It’s with this value chain that problems are answered, and action is taken after the analysis. The took the process further by introducing examples from Harrah’s service to growth analytical model and McKesson Pharmaceuticals supply chain analytics. Both organizations recognized a problem or determined an initial goal, they went through similar value chain processes before branching even farther to specifically benefit their organization. Business analytics is an essential part of any successful business.
I really enjoyed the Google video this week because it gave insight into a field that can benefit greatly from analytics and data management in the initial stages of implementation. It seems obvious that Human Resources departments have an ample supply of data on employees, but it was interesting to see the many ways it can all be used, especially in a tech giant like Google. I was intrigued by the Organization Structure or Design analysis Google did when trying to decide how they should hire and promote to grow the business. The simplicity to the idea caught me somewhat off guard, not to say it’s easy but the fact that very little detailed information can be used to demonstrate and visually show the data to make an informed decision was amazing. The fact that Google can bring in cold hard numerical data to prove or disprove myths about the company is an invaluable tool. Too often myths or rumors come up in organizations that cause a toxic environment. Seeing that Google has taken statistical steps to avoid this is great.
