Businesses that have successfully acquired data and found ways to derive greater values from information as simple as names, addresses, pictures, and videos to relatively trickier data like users’ GPS coordinates and your computer’s browsing history which could require users’ consent, have thrived in this new age world. Even a scary pandemic like Corona that pushed almost all the earth’s population behind closed doors, only got some businesses even more innovative to make the best of the newly available avenues of data.
So, businesses that use data as a key ingredient to their decision-making and hence rely heavily on the freshness and accuracy of data they consume must pay close attention to (a) source, (b) quality, and (c) cost of data. If the source of data is a system or process that requires human interventions, the credibility of such data can be questionable which could negatively impact the business. Sometimes that is the only option available to businesses and hence they proceed with taking that risk knowingly and hoping that the checks and balances in place (again mostly human-driven) would take catch these in time. Related to this point is the second factor i.e., the quality of data. Just because the source of data is a machine and not obviously error-prone humans, businesses can not assume that the quality is acceptable. A system holding an email address of a customer as [email protected] could actually be sending the emails to an entirely different person with the email address [email protected] only because Google does not consider the period (.) in the email addresses as part of the email. Subtle, yet can be an expensive error. Ultimately, all this boils down to the cost of doing business. How much is a business spending on ensuring the data from the source is thoroughly checked, cleaned up, organized, and presented in the right way at the right time so the decisions based on these inputs do not turn out to be flawed? Businesses with deeper pockets spend lots of money on hiring great talent who would in turn (hopefully) put in place the right tools and systems in place to make the best of incoming data.
However, deeper pockets are not ubiquitous. Hence, for many, the data that started out to be an asset could become a liability due to poor quality, lost customers, declining revenue, and increasing costs. The fine balance between quality, credibility, and costs can be assessed through some of the questions we believe businesses must ask themselves –
- Have we established metrics to calculate credibility, quality, and cost of data acquisition?
- Where do we stand against the benchmarks for the industry we are part of?
- What improvements were targeted and achieved year-on-year for data acquisition?
- What is the cost of bad data to our business?
Technology is a great savior and once again we can turn to technology to help those who want to upgrade their speed, quality, and economics of data acquisition. There is no dearth of technologies, but systems and solutions carefully designed to solve specific business problems in a scalable way aren’t many. Productized off-the-shelf software often does not meet the customers’ unique needs, requires extensive maintenance costs, is complicated to accommodate newer business use cases, and mostly ends up requiring some additional effort to take care of zeroth mile or last mile data stream management.
For the past 15 years, the founders of Bydek have continued to work very closely with businesses across industries, regions, and sizes towards helping them to continue to keep data on the asset side of their balance sheets in uniquely creative ways. Ask us for a comprehensive scorecard created through a data assessment for your business function. We promise you will not be disappointed.
