Kaan Turnali, Global Senior Director of Business Intelligence at SAP writes about adding more insight to sports through mobiles dashboards.
When it comes to sports and analytics, I see two main slices of the pie: the game where it all happens and the operation that supports the organization. There is a lot written about the former; however, the latter may be overlooked because of its distance from where the action takes place.
Sure, winning the championship may make up for all other business decisions, but as I wrote in my post Fan Experience Matters, at the end of a long season, only one team gets to go home with the trophy. Therefore, I subscribe to the notion that operational excellence is as critical to the execution of the sports organization’s strategy as any game-winning move.
At their core, sports and entertainment organizations operate as business entities and just as, for example, a retail business would do, they seek to increase their revenue streams while reducing expenses and to keep their customers (fans) happy by delivering the best products and services. Therefore, they monitor some of the same type of KPIs that traditional businesses analyze.
In this context, when we think of the role of executives that lead sports and entertainment organizations, we recognize that they share the same basic needs: They seek insight into business data in order to define and execute the strategy, and they require effective measurements, which allow for adjustments and timely course correction ahead of obstacles, no matter how big or small (because sometimes a pothole can be as costly as an iceberg).
If business intelligence (BI) is going to enable faster, better-informed decision making, it needs to fuel growth and profitability. At the executive level, dashboards can play a role in providing quick and easy access to key metrics. Just as a pilot must know immediately if there is a change in one of thousands of functions that make up a plane’s complex construction and performance, sports and entertainment executives require similar alerts as part of an integrated advanced warning system, so to speak, before it may be too late for any corrective action.
If a picture is worth a thousand words, in analytics a proof of concept that harnesses the power of rapid prototypes to limit the risk and accelerate collective learning as part of the design thinking philosophy of “Fail early and often” is priceless.
Let’s get ready for a quick PROOF OF PLAY!
First, we need to describe the business scenario, so let’s create a hypothetical baseball team: the Jacksonville Tigers. (Disclaimer: Any resemblance to teams living or dead is purely coincidental; I chose Jacksonville because it is near the ocean, which I love, and named the team after my beloved cat, which is no longer with us).
Second, let’s assume an operation with four key revenue streams: 1) ticketing, 2) merchandise, 3) concession, and 4) digital media (sponsorship and advertising).
Third, let’s select two measures. Let’s assume that we are interested in revenue and attendance figures. (By the way, we won again last night in front of a sold-out crowd.) At minimum, we want to look at revenue across the five dimensions, study attendance trends, and drill down for further analysis if needed.
Everything starts with the concept of a home page, which serves as the single point of access for all analyses the executive would need. The user interface provides a self-intuitive navigation with already familiar functionality. The design is neither crowded nor overwhelming. The dashboard is both engaging and easy to use. Nothing on the real estate is random; instead, every dimension and measure has a purpose.
But most important of all, it provides actionable insight. This means that before I even select or tap on anything, thanks to visual alerts, I immediately see results that require more scrutiny.
In our example, I notice that despite a sold-out crowd, overall merchandising sales fell short of game-day targets. To find out more, I drill down into another mobile report with the ease of a single tap and find out that it is due to below-average sales of one of the high-margin product lines. So, I immediately highlight the concern on the screen and email it to my VP of merchandise directly from my mobile device. I want to know, is it because we did not get enough shipments in time, or is there another, more serious problem with our supply chain, a problem that may impact future sales?
This is one of many scenarios. There’s also the ability to dig deeper whether we are looking at the current value (last night’s game), comparing it over time (this season’s average vs. the last five season averages), studying comparative measurements (for example, last night’s figures against any other team vs. the average when we play against the same team), or identify effectiveness of marketing campaigns.
When we think of other analyses, even if it involves only these four dimensions and two measures, the questions we can ask are boundless. I strongly believe that when it comes to turning data into insight, often our imagination and ingenuity may be more important than anything else in order to make it happen.
Mobile dashboards, when designed and implemented effectively, should should provide actionable insight by highlighting problem areas for proper and timely discussions to take place among the right teams so they can execute on all three cylinders of analytics: 1) insight into the right data 2) for the right role 3) and at the right time.
This is the value proposition of mobile BI and power of mobile dashboards.
About the author:
Kaan Turnali is a Global Senior Director, Business Intelligence (BI), for SAP’s Global Customer Operations (GCO) Reporting & Analytics Platform, Kaan is responsible for the development, oversight, and execution of strategy for the BI platform across GCO’s worldwide user base. In addition, he manages special mobile BI projects for the Office of co-CEO Bill McDermott and the GCO senior management team. His background and experience in the integration of business and technology span over two decades. He is also an adjunct professor, teaching BI in the doctor of business administration program at Wilmington University. Read more at http://www.turnali.com/ or Follow @KaanTurnali on Twitter or on LinkedIn
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