Loading MikesBikes after 5pm on a Thursday can give you a fright for two reasons. One, you are desperately anxious to see where your teams sits in regards to shareholder value - did we increase? Did our investment pay off? Did the dog tell us we are doing 'good'? Once that horror is over - for even if you team has done badly, to know bad news is better than to know no news - the second horror is coming to terms with the unpredictability of others teams.
Being exposed to my own industry only I cannot speak for others, but I have noticed this week in particular the alarming rate at which teams can shoot up or down in what seems to be a haphazard fashion. A few weeks ago we witnessed a team in last place with a negative profit suddenly shoot to first in the next rollover. This type of thing can unhinge you a little, as you feel like you can never feel safe writing a team off. When I look at teams that suddenly drop in SHV I now ask myself one question: are they sitting down the bottom in a well, or on a springboard?
This brings me nicely to the inescapable concept of analytics discussed by Davenport (2006) in this week's reading. Judging by their examples, I have whittled analytics down to two key factors: numbers and questions. If you can ask the right questions and understand the numbers, you are on the right track to an effective analysis. As a psychology student, it was pleasing to see Davenport (2006) cite experiments as a commonality among analytical firms, used in these cases to measure the impact of an intervention strategy. This reminded me of a key concept I learned in marketing earlier this year, that both effective and ineffective strategies should be examined with equal intensity. Too many companies, I believe, spend a lot of time focusing on what went wrong, whereas when an intervention succeeds there is little analysis (or little depth) conducted to discover why it worked.
On reflection I notice a similar occurrence in my own team. When loading the dreaded rollover results for the past two weeks we have been pleasantly surprised with the outcome, immediately contacting each other to share our joy. When we meet, the first thing we discuss is how happy we are and where we stand next to the competition, including identifying which teams we see as threats. What we perhaps don't do enough is focusing on the changes we have made from one period to the next and asking why they worked. So our shareholder value increased by 20%, why was that? Did our advertising differ from year to another? Was it increased sales from the new modification we launched that caused profits to rise? Likewise I think we need to work on extrapolating these analytical questions to involve other teams, for example taking our closest competitor and examining the changes they made from one year to the next in an attempt to identify the key factor(s) that led to their improvement. Adopting this approach in future may help to shed some light on the changes in SHV rankings between rollovers, and may help those crazy, colourful lines that seem to dart sporadically across the page to make a little more sense.
Davenport, T. H. (2006). Competing on analytics. Harvard Business Review, 84(1), 98-107.