Data services are just like coats - not all are created equal. There's a varying range of price, quality and reliability. And, if your data doesn’t have a good coat, there could be a range of bad or costly decisions made. These decisions could affect the business performance, financial situation, risk jobs, or even the fate of the company.
Let me put it this way, you wouldn't go out in freezing temperatures without the appropriate coat, and you definitely shouldn’t work with data or make business decisions without the same level of protection. In this case, that’s accurate data.
Quality Data Services
And, just like with coats, there are different levels of quality data services out there. The low-cost option might tempt you, but this is cheap, fast fashion. It’ll barely last the season before it’s out of style. And it definitely won’t protect you (or your data) from the elements.
Not to mention the fact you’ll definitely need to buy another the next time winter comes around again. It’s the same with data - if you don’t invest in good quality service, you will end up paying twice as much, if not more, in the long run to fix the earlier mistakes.
You might be tempted then to invest in the high-end option. But you’ll probably need to remortgage just to afford the designer label. It’s also probably totally impractical, has complicated care instructions, and you’ll be too afraid to expose it to the elements - what use is that?!
So, where’s the middle ground? Well, last but by no means least, there’s your favorite coat. It’s with you through thick and thin. It is protecting you (and your data) from the elements. It’s dependable, reliable and always in style!
So, what does this C.O.A.T. do for your data? Well…
Generally, data is used by many people or teams, which can lead to multiple classifications of one product. For example, one person might put DHL as a courier, while another might log it as logistics or warehousing.
A taxi might be classified generically as travel when it should be classed as Travel > Road Transport > Taxis. Also, a project cost should be assigned to the same budget or GL code, not several. It could even be a simple as units of measurement.
One person may use Liter, another “Ltr” and another “L” – but these should all be one format. This means everything can be reported accurately. You get an accurate picture of what’s going on, and better business decisions can be made.
Data is only useful if it’s organized. Think of a messy closet, you’re looking for your favorite top but can't find it as everything has been thrown in there. And, much like your closest, you can organize your data in different ways. The organization of your data depends on what you want to get out of it, and that will produce various reports/analytics.
You may want to assign data to employees, teams, departments, functions or internal categories. Also, time periods such as months and quarters, or year groups like P1, P2 can be assigned. So, for example, when you need the information on the accounts that Sharon in Finance is working on or the sales teams’ performance for the quarter - you can pull that information quickly.
This can mean different things to different people. At its most basic level, accurate data is correct. In more detail, this could be no duplicate information; accurate invoice descriptions; correct classifications; no missing product codes; standard units of measure (e.g., ltr, l, liters); no currency issues; correctly spelled vendors; fully classified data; or the right data in the correct columns.
So, what does this mean? It means greater visibility across your business in several areas, allowing better decisions, as well as time and cost savings and increased profits.
This is critical. Business decisions around jobs, staffing, budgets, cost savings and more are all based on data. Data is used by everyone from the bottom to the top of an organization. You have to be able to trust that what you’re looking at is the right information. You need it to be accurate in order for your teams to use the data in their daily jobs.
If they don’t trust the data, then they might not use the fancy new expensive software you’ve just spent tens of thousands of dollars installing. Or the new AI you’ve installed may not produce the right results because it’s learning from dirty data.
Like a good coat, data is an investment - not a cost. By making sure it has its C.O.A.T. on, you’re saving time, money and avoiding future problems. And also like any coat, it needs to be maintained. You need to continually ensure your data is consistent, organized, accurate and trustworthy to get the most out of it.
So, which C.O.A.T. do you want your data to wear?