This may seem an odd question as our society becomes more and more reliant on data. However even as a highly skilled analyst who lives in the world of data I have recently been on the end of a totally useless decision because it was based on poor data.
Let me give you 2 outcomes to the same scenario and let us analyse our business options
Scenario The sale of a house. For most people this is a major asset and therefore they want to take the best advice and need to review the mode of sale, the best representative etc.
The best way to make decisions would be based on data available such as:
- What are similar houses selling for in your area and look at this is a date based review, and compare this to market movement e.g. is the market going up or down in your area as a standard.
- Company: the sales company you are using, what is their expertise in selling your style of house in your area, and the person representing you, what experience do they bring to the table.
- Marketing: When other properties have sold that are similar to yours in your area, how were they marketed, and which style do you think you are best to follow.
- Sales Mode: Once again review houses in your area and look at how they were sold, Auction or Direct Sale. Put a price on the advertising or not. Make a choice.
So now you your research you are ready to put the property on the market. Quite often the sales companies will present this research to you if they are a quality company. If you are lucky you will get an offer and quickly for your home, but if not, you are now reliant upon making decisions based on direct data regarding your property.
This is where my question above starts to take effect. Up until now, as a vendor you are make choices based on firm factual decisions. E.g. actual sales and actual facts. Now you are asked to make decisions by the Sales Company based on what they present.
So let’s look at what is collected as data.
Is the collection of data based on set standard responses, or is this purely notation which has been interpreted by one or more employees of the Sales Company? Measure for Data Quality Note only by client 70% value, Note only interpreted by Sales Company to fit a standard 50% value.
If the above is factual, how many of these notes are from prospective genuine realistic buyers, e.g. those looking in the area for a home similar to yours. Do this as a percentage, e.g. if you had 20 people through look at how many considered offers, ask questions of the land agent etc. for each one that does, that could be considered a prospective genuine realistic buyer, the rest are not. So this percentage will have a major impact on your information. For the sake of this exercise, we imagine 50% of the people are genuine.
Finally, how many actual offers have you received? How many people that your sales company has met and shown your house have been interested enough to put in an offer? If this is zero, then you need to go back and review your marketing, sales mode, and Sales Company. Review if the data presented to you or gathered for you was correct.
So my conclusion to Data. There was an old statement I once heard Garbage in, Garbage out, and this is true. If the data you collect is Garbage then the information you give is Garbage and using this for making decisions is really not the wisest of choices. Look at the data, review its worth, and then elect the path to your decision. This path may change nothing, it may be to review an initial decision and make a different choice. Don’t however ignore data, and don’t put full weight in the data if the data is of poor quality.
This scenario is not the only scenario of this type. There are many business decisions made on a daily basis based on data. Your job is to get the best possible data and for you to critically analyse the data given to make the best possible choice.
Cate Schafing is a successful Australian business woman in the IT field serving as CEO of Accede Holdings Pty. Ltd. makers of Ezymeetz, ICE and Virtual Gym. She develops innovative new technological products as a programmer and entrepreneur. In gratitude for her success her company supports NFP’s by donating $5000 per month in programming time for NFP’s requesting work.