Killer Technique 10 – Capture Only the Data that you Need

Killer Technique 10 – Capture Only the Data that you Need

Killer Technique 10 - Capture Only the Data that you Need January 25, 2018 Collecting data in one form or another is a matter of course for most job functions across most industries today. From reports and logs, customer and prospect data, applications and appraisals,...
Killer Technique 9 – Resourcing your Projects

Killer Technique 9 – Resourcing your Projects

Killer Technique 9 - Resourcing your Projects January 25, 2018 Professionals from wide ranging job functions face the challenge of managing often multiple projects, requiring fluctuating human and technological resources which most professionals don’t have at...
Killer Technique 8 – Successful Online Inventories

Killer Technique 8 – Successful Online Inventories

Killer Technique 8 - Successful Online Inventories January 25, 2018 Don’t lose out on customers because of inaccurate or out-of-date product information. Managing your online content in a timely fashion can be the difference between a sale and a missed...
Killer Technique 7 – Handling Difficult Data

Killer Technique 7 – Handling Difficult Data

Killer Technique 7 - Handling Difficult Data January 25, 2018 All organisations have what we call ‘dirty data’. it’s the type of unprocessed data nobody wants to take responsibility for.Whether the data is problematic to process, vast in volume or...
Killer Technique 6 – Maintaining a Clean Database

Killer Technique 6 – Maintaining a Clean Database

Killer Technique 6 - Maintaining a Clean Database January 25, 2018 Estimates suggest that 30% of B2B data goes out of date within 12 months, and with over 1.3 million people moving home each year, it is tricky yet essential to keep your database up to date.An out of...
Killer Technique 5 – Inaccurate Data Pitfalls

Killer Technique 5 – Inaccurate Data Pitfalls

Killer Technique 5 - Inaccurate Data Pitfalls January 25, 2018 A recent survey conducted by Experian showed that on average, organisations believe ¼ of their data to be inaccurate, having a direct affect on their bottom line.The result is wasted time and money as well...