I have been in Microsoft Finance since 1994 doing analysis and leading teams, in support of very different leaders, from call center managers, to area sales lead and developer managers. I have always been immersed with data, and I have always been obsessed with being able to synthetize it and help my business partners make better decisions.
As Steven Few pointed in one of his posts, industry has dramatically improved the way we processed data over the last 15 years. When I started as a call center analyst in the mid 90’s, I could only run a query over a limited set of data for the US on Mon/Wed/Fri between 9 am and noon. We quickly made progress in that area with data warehouses & OLAP queries.
I also quickly discovered the critical importance of taxonomies and hierarchies, as we were consolidating call centers at Microsoft. I remember spending hours defining consistent taxonomies on KPIs like minutes-per-call, and I saw it all payoff years later when minutes-per-call meant the same for any call center, regardless of whether it was located in China or Germany. We spent hours deciding, for example, if we should include or not include our calculation of minutes-per-incident, the support professional manager’s time in overseeing how resolution of the call was going. This, in my mind, should always be the first step and probably the biggest area of investment and governance. We shouldn’t talk about technology until we have spent a huge amount of time agreeing on very detailed scenarios that impact all our critical KPIs. Data quality starts first and foremost with consistent and accurate taxonomies.
Getting access to more data with greater quality was a great breakthrough, and it really improved my job satisfaction as I could give much greater insights to our business partners. I still remember the day when I gained access to each individual call, as I had only been getting aggregations and summaries until then. The first thing I did was simply build a nice minutes-per-incident distribution to see what percentage of our calls was less than 50 minutes and what percentage was greater than 2,000 minutes. This helped us understand what was impacting our overall average minutes-per-incident, a key KPI for call centers.
The art of analysis is really the combination of making comparison and dramatic improvements in data processing, combined with strong taxonomies. Good hierarchies meant that I could give a lot more insight. I could compare different call center utilizations and cost-per-minute, which really helped us in our decision-making process with respect to key investment in the Indian and Chinese call centers.
In the mid 2000’s, I started developing a passion for data visualization and storytelling. I was fortunate to work closely with superior storytellers who deeply appreciated the art of making things simple without making it simplistic. I started reading books from Tufte/Few and followed data visualization blog experts. I was so passionate about these 2 fields that I decided to teach classes at Microsoft on data visualization and storytelling, which also help me tremendously overcome my fear of public speaking. (Hint: The best way to overcome the fear of public speaking is talk publicly about something you are passionate about.)
Together, all of this meant that I improved at being able to tell a story and pick the most effective visuals to synthesize data and make it consumable. However, our tools were not always easy to use. You could effectively make Excel do anything you wanted, but it still required a lot of work to build pivot tables and graphs, and to copy/paste them in PowerPoint slides. Things looked great, but it was still a static process that took time every month to go back to and update. This is something that I tell customers: for 17 years, the BI I created were pictures of Excel that I pasted in PowerPoint slides. PowerPivot was a great breakthrough in making the power of SQL available to non-technical expert folks. You could easily mash up data and use filters to interact with the data easily. It was an improvement, but we still struggled with the process of moving from data exploration to data presentation.
In 2012, I discover a product that changed the way I did my job. This was not an evolution but a true revolution. I remember seeing a demo by Amir Netz and thinking that I needed to get my hands on the beta software. Luckily for me, at that time, I came across of couple of French compatriots who worked in the teams that were building this product called Crescent. As I started playing with it, I immediately saw the possibilities, not only in terms of data exploration but also with data presentation. This is an important point because my ultimate goal was not to give insight, but to drive impact. This is why storytelling and the ability to influence is a key aspect of the ability to make an impact. The fun and difficult part of being an analyst is that it requires technical skills and social skills. Power View integration with PowerPoint was remarkable because I was then able to create dynamic slides that changed as I presented in business reviews. In addition, I didn’t have to get back to people on issues, and I could answer their questions in the meeting by simply changing the filter or building another view on the fly. All of this is great news for analysts.
At Microsoft, we used to have a design challenge and a technical challenge, but since, the company has removed all the technical barriers, allowing us to only focus on our design challenge. Power View is incredibly easy to use and within days we had dozens of finance folks at Microsoft building very powerful views. The challenge now is to make all the data “consumable” and to be able to synthetize effectively with the right visuals. We don’t have technical challenges anymore, as we can now fully focus on the most important issue: how to convert data to information and integrate that insight into a logical and well-structured story that can be easily consumed by business leaders.
I personally believe that Power View will have the same impact on business as Pivot tables. This is another great advancement, as we are moving from breakthroughs in the way we process data to breakthroughs in the way we convert data to information. The ability to hold a variable constant and to see the change in the context of the overall picture is one of the most critical aspect of any analysis. The ease-of-use of the product out of the box is incredible, and the business reviews have evolved from rigid lectures to dynamic conversations.
So take Power View for a spin and see what you can do with your data – Power View has changed the way I do my job, and it can change the way you do yours too.
For a more in-depth view of Power View, please see Part 1 of this From Data to Insight & Impact series, featuring my interview with Microsoft Corporate Vice President Susan Hauser about how her team uses Power View to get deeper insights in a shorter period of time, and Part 2, which presents a tutorial on how to build a sales summary with Power View.
By Marc Reguera, Director of Finance, Microsoft