Beginners' Guide to Self-service Analytics

Ok, maybe you’ve read my previous article >> about spreadsheet inadequacy to run an entire business, and decided to ditch your beloved Excel reports, aiming to surf this data-driven wave. As it is, you might have realized that these days there is much more to measure than financial information. You also understand that graphics (data visualization) convey messages much more effectively than text and numbers. The natural path is to adopt a self-service analytics tool, no matter if your company is tiny or huge.
But where to start? Read along, I’ll do my best to recap in the minimal expanse of words and concepts a sort of “starter kit” to get business improvements through data in your own organization.

I’ll borrow this one from Gartner’s IT Glossary:

Self-Service Analytics is a form of business intelligence (BI) in which line-of-business professionals are enabled and encouraged to perform queries and generate reports on their own, with nominal IT support. Self-service analytics is often characterized by simple-to-use BI tools with basic analytic capabilities and an underlying data model that has been simplified or scaled down for ease of understanding and straightforward data access.

Clear enough, I’d say… except perhaps the last sentence. In essence, it means that the system must feed on reliable information, ready to be converted into useful and -more to the point- actionable insights. In real life, though, that’s hardly the case. We’ll see more about this later on.

You should know by now how much and in which ways Business Intelligence contributes with in any kind of organization (otherwise get a refresh here >>); moreover, if a DIY approach is taken you’ll get:

•       Performance boost in every area of the business: quickly detect operational problems, surges in demand for certain destinations/products/services, check ROI in all marketing channels at once, uncover hidden business opportunities, and a very long etcetera.
•       Big picture served in a golden plate: up to now, you were forced to analyze your company’s performance through several independent systems (see previous). That’s like attempting to understand a whole movie by seeing pictures of it! Hence, no more “data silos” in which information was trapped and lost its usefulness.
•       Huge time-savings: think how long it takes to process and study those old spreadsheets, not to mention Google Analytics stats, CRM, financials… Isn’t it great to have all that info in a single place, just showing what’s really important?
•       Active rather than reactive initiatives: knowing future trends and calculating accurate forecasts will help you anticipate market needs. No more following the hotshots!
•       Automatic alerts:  in case certain thresholds are violated, a SSA tool would let you know immediately. For instance, if a certain client is not selling as it used to, or if a competitor decreased their prices…
•       No IT involvement: until not long ago, BI tools where ridiculously expensive, yet needed the intervention of IT specialists not only to use them but even to infer what was the story the data was telling.
•       No meanings lost in translation: if you had to rely on IT experts as per item above, unless they where acquainted with your business (almost impossible), there would definitely be misinterpretations and wrong assumptions.
•       Big Data democratization: as your company grows, so will its data sources. Can you afford a team of data scientist to manage such a monstrous amount of information from different systems? Didn’t think so.

Bottom line: you’ll be able to opt for confident, timely and (almost) error-free choices. There is no totally faultless decision support system though, but we’re working towards it.  

Then market is being quickly filled by all kinds of specialized tools these days, so it all sums up to ease of use, uncluttered interface, extensive connection capabilities, good support and -of course- price. There are even free desktop versions of well-known brands, however their limitations generally prevent usage in business environment (except for experienced data jockeys), and being physically installed on a machine make such systems impossible to use on the move.
A cloud-based solution would be ideal, since there will be no infrastructure or maintenance costs (have you got any idea the kind of machine you need to run millions of queries each day?), you’ll use as much features as you need and risk is minimal, since you can cancel subscriptions at any time.
But no matter what option you select, you’ll have to check and prepare your data first and foremost.

Among the advantages of self-service analytics, I mentioned the unnecessary intervention of IT staff, and I still stand for it; however, you must be rather familiar with the data to be analyzed, as well as prepare it a little bit before scrutiny, because chances are you don’t have ready-to-use data. If you manage only a handful of spreadsheets or the odd database, maybe a CRM, ERP and some website usage logs, I bet you’ll be able to prepare the data yourself. If, on the other hand, there are several sources of data which require some manipulation before exporting usable data, or connecting to the SSA system is somehow not straightforward, or if the exportation of data is not an easy task, you might need some expert guidance ONLY for the SSA system’s initial set-up. Afterwards, it is probable you’ll be able to do it yourself too. Be aware that good SSA tools are also able to automatically connect and import the relevant information from chosen sources, even automatically preparing your data… although that may mean a steep increase in the bill.

Before engaging in analytics, then, you should ask yourself:
Quality – Are the systems from where you pick the data up to date? In the exported files, are numbers stored as numbers, dates stored as dates, and so on?
Preparation – If one or more of the questions above get a “no” for an answer, data “cleansing” (possibly data “wrangling” as well) is a must before analyzing, otherwise you’ll end up trusting wrong conclusions. Maybe the first couple of times it will be a bit difficult, but once you get the hand of it, it’ll be a breeze. Then again, you can count on somebody in your staff, or the same SSA system can automatically conduct data preparation for you.

Conversely, if you don't know what kind of data you're trying to analyze, how to extract it from several systems or if you’re not sure you have the right kind of data, you’ll definitely need consulting services to get you started (REVVA can provide a free initial assessment, should you be interested).
But that’s about all there is for bad news: once the SSA tool is set up, you can sit back and… relax? Not yet, there’s still one final step before true data-driven money-making.

Sales volumes and profitability are important, but might become what in “lean” methodology are called “vanity metrics”. Increased general sales figures might be good news, but you might be missing out an important decrease in sales for certain markets or products. The same can be said for profitability measures, just to pose an example. So it’s a question of deciding which KPI’s (key performance indicators) are important to you, and -more importantly- how will they be actionable. Because there is little reason to measure whatever cannot be acted upon!
It would also be a good idea to keep an open mind: you surely know your business upside down, but I bet you’re not used to explore your data. In fact, REVVA consultants might point you towards certain aspects that were missed so far, be it on website usage, marketing campaigns, operational procedures, etc.
In short: KPI’s shouldn’t be fixed and eternal, they can and should change as your company grows.

BI software is becoming a must-have in any organization, offering a solid evolution towards in-depth knowledge about the travel industry, competitors, market, customers and suppliers, just to mention a few metrics. Current technology adoption makes it impossible to survive without connecting to myriad of different systems, all of them processing disparate kinds and volumes of information. It is humanly impossible to analyze all that information at once to obtain actionable insights, so either you count on a team of data experts and IT professionals, or you adopt a low-cost/low-risk easy to adopt solution like REVVA.
Check it now >>, find a solution suitable for your business and start converting data into money.

Thanks for reading!

Marcello Bresin