Einstein famously said, “Not everything that can be counted counts, and not everything that counts can be counted” while Count Von Count (pictured above) said “That’s TWO! Two worried frogs! Ha ha ha ha!” Einstein was right in so many ways, but I believe that in the context of small businesses and startups, the Count was the one who truly grasped the full import of collecting and leveraging business intelligence data. In today’s world of software and data, it is so easy to count everything which might be of value, that there is no reason not to. The trick is in how you leverage that information, and how you design access to it. In other words: count everything you can, but take the time to determine how to prioritize that which you do count, and what to pay attention to when you look at that data.
As I have discussed here before, I am a proponent of a goals-driven framework for business strategy and tactics. I believe that strategy should be devised to help meet meaningful goals and that tactics should be implemented to support the strategy. The key ingredient in goal-setting is a defined metric, and the ability to measure progress towards that goal is via (duh) the data that must be tracked and gathered. In the absence of meaningful information, decisions can easily be made for the wrong reasons and priorities can be improperly set; managers need to make rational decisions and let those decisions be driven by data first, and intuition second. Many owners and managers of small businesses find that they make their decisions by instinct, that they “fly by the seat of their pants,” often in the absence of the meaningful data which should help to drive those decisions.
Here are 5 tips for gathering and leveraging data to drive a rational approach to defining and meeting goals and formulating and executing strategy.
1. Debate and strategize. First determine what it is you are trying to accomplish and how you intend to get there. it could be something as simple as increasing revenue; improving the monthly traffic to your site; or gaining a better understanding of your customers to improve satisfaction. No matter what it is, first debate with your team exactly what the important goals are, and make sure they are measurable based on the data you have the ability to collect. Set a strategy to accomplish the goal: more revenue? Maybe the strategy is to increase lifetime value of your customers, or maybe it is to increase per-order revenue. More traffic? maybe the strategy is to improve word-of0mouth. Better customer satisfaction? Maybe the strategy is to reduce wait times for customer service requests. In any case, measure, measure, measure.
2. Collect and organize. This is a process which can be as difficult or as easy as you make it. At crowdSPRING we have a database that is fairly easy to query and a process for creating new queries quickly. This allows us to set up simple tools to pull specific types of data using date ranges. For instance, we pull a weekly report on all new projects posted, which includes some immediately useful data (how many projects were posted last week, what was the value of those, which buyers posted them) and some data which might come in useful later (time of day the project posted, IP address of the buyer, date/time of buyer’s registration on the site) . This data is aggregated in a spreadsheet, which allows a quick update every week.
3. Sort and prioritize. The data collected must be sorted to be useful; for instance the New Projects report I mention is default sorted by date and time, because it is our priority to understand projects and revenue on a daily and weekly basis. If it were our priority to understand average award in projects, we would default to that.
4. Display and visualize. Different people look at data differently. I tend to consume mine best in the form of a chart or a graph, while Ross prefers to eat his data raw, just the numbers in front of him. Excel and other spreadsheet programs give you simple and powerful tools for setting up charts, graphs, and tables, and these can be leveraged in ways which make analysis simple and fast, which leads to the next point:
5. Analyze and theorize. Data in a vacuum is meaningless; we use the data we collect to measure our progress against goals, and to determine the efficacy of our strategy and tactics. Some analysis is simple (how many projects posted last week), but it can get very complex. We typically theorize the impact a new tactic will have on our progress towards a goal and we then measure our progress from the date of that implementation. This analysis helps us to determine whether to continue an effort, abandon it, or modify it. When a small business is constrained by its own capacity (as so many are) it is critical to know when to move on.
Collect your data – all of it – but use it to serve a greater master: your goals and your strategy.
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