“Good data in, good data out.” How many times have my fellow data management folks heard that?
So really, what is good data? In the course of my experience as a data manager and leading data management teams, it really depends upon who you ask: “Good data is timely.” “It is accurate and complete.” “It works in all my applications without issue.” “Its coverage is broad and deep.” “It is anticipatory.” “And, it is consistent.” But we all know that the definition of good data is not that easily defined.
Timely. Accurate. Complete. All Critical factors in Their Own Right.
Timely is in the eye of the recipient: If you’ve got a client in Sydney, you had best keep an eye on the clock. If you’re in New York, remember that as your day closes out, their day is about to begin. You always have to know where your clients are versus the clock. Saying you’re an end of day service doesn’t absolve you of not understanding that your business day definitions can be completely different. Timely also relates to downstream dependencies that you may not even be aware of as they are outside your purview. Your ability to have the data available when the end user needs it – in conjunction with other requirements – will win over your client. There are reasons people ask for SLAs and these data drivers are usually at the core.
Accuracy is defined by who is using the data. Most end users will say they must have 100% accuracy. Data managers chase the elusive 100% mark each and every day. So how do you achieve it? The key to accuracy is understanding your clients’ needs: What are their requirements for ensuring maximum returns and, minimum data headaches, and what is the process in place to ensure those requirements are met every day? The other key is making sure the entire process is transparent. If someone downstream wants to understand your source and methodology – tell them! Show them where the data is coming from and what happens to it from start to finish. The more transparent you are the more comfortable your clients will be. Make a change to data intraday without proper notification and sit back and wait for your phone to ring. No one in the financial markets ever wants their data to change out from underneath them. There are already so many moving parts that having something change that’s not anticipated can be a disaster.
And finally: Complete. Everything has to be done prior to market open each and every day. I had to sit next to a trader at US market open each morning, and if they didn’t open clean – LOOK OUT!
I’m afraid that even when it comes to consumption, you own it! It’s really up to the data management team to provide the firm’s golden copy of the data universe defined in conjunction with the business. Reports and models being generated from your data set will be known and related expectations will be well understood. It’s really up to the data to deliver. Your data will take on all shapes and flavors and go through potential models and not look anything like what it started out as. It’s still your responsibility as the data steward to ensure that the output your clients receive, ultimately meets their expectations.
Achieving the Data Utopia…with a Data Plan
So what’s the plan to get to this utopian state? Bundle, unbundle…outsource, in-house…so many options. That’s why a plan is so imperative. Before you even think about touching the data or updating a record – make a plan. The time spent will pay off. Understand also that clients’ requirement are critical here. What does the client really need? Take data coverage for example: someone simply saying they want global equities, which at first glance seems simple, may or may not be. Is it developed markets? Is it adjusted or unadjusted? Is it simply any closing price or is it primary exchange close? What is the coverage and related data attributes required for your clients? Are you a hedge fund that needs FX data? What time do you take those very important FX rates? Close of the London trading day? Close of the relevant trading market? Both?
How will you handle client requests to see future state data, or look back at a moment in time? Can you meet those requirements? Many service providers can do previous day but what about, for example, the impact of the eBay spin-off of PayPal on your holdings? These are complex requests and all should be considered in discussions. Often times, an index provider will include two different lines of stock – one to represent the shares prior to an event and the other representing the post event line. Can your performance system accommodate these variations? Not understanding and planning ahead for the nuances of the individual global markets and respective event driven changes could be financially impactful if they’re not handled correctly.
Getting it Right and Proving It!
Consistency in delivery and definition - getting it right from one day to the next and not just randomly keeps the business running smoothly and allows everyone to focus on their primary function instead of yours! And remember, it is really up to the data team to prove they’ve gotten it right. Prove it, and not anecdotally, but through well-defined metrics. The insight will be well worth the effort. Tracking these results will provide you great insight into your processes as well as show your client you’re focusing on what matters by closely monitoring critical issues.
And So in a Nutshell
- Partner with your internal clients to fully understand your firm’s business’ requirements.
- Work with your clients to understand their needs across all critical factors - tell them what you understand those requirements to be, and then deliver it.
- Once you’ve reached an agreed state – make it happen.
- And prove it! Produce data results metrics and review them with your clients on a regular basis.
If you can achieve the above, you will have a product that works for your business, you will have data that is timely and accurate, with requirements that are understood, implemented and delivered consistently. Best of all, your bottom line will positively reflect all these efforts. And that is exactly what a data person wants! In the end, it’s not about the models or the super speedy technology or the slick graphics…it really is all about the data!
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