Is Bad Data Hitting You Hard? Here’s How to Roll with the Punches
You don’t need an authority to tell you that poor data quality data implies a multitude of negative consequences in a company. It has a ripple effect. It creates competitive disadvantage, bad strategy, lost productivity, customer relationship and financial loss.
Common complaints include incomplete data, outdated records, inaccurate records, duplicate data, and typographical errors.
Let’s put things in perspective. In marketing, bad data make it more difficult to know the potential client. In procurement and logistics, bad data send deliveries off in the wrong direction. In manufacturing, bad data means components don’t fit together properly.
Want to anger a customer? Work for a mobile phone company, and send him or her an incorrect bill. It happened to me several times, and believe me, it’s a mood changer.
Poor data can result in missed opportunities – causing your business to fall behind competitor launches because your data didn’t show the trend. In short, accurate data makes things simple, while bad data makes everything complicated.
Now take a look at these stats provided by the Harvard Business Review:
- 88 % of all data integration projects either fail completely or significantly over-run their budget tweet this
- 75 % of organizations have identified costs stemming from dirty data tweet this