If you’re reading this, chances are you’re not the average travel industry dweller. Except perhaps IT gurus and bus drivers, everybody’s on it for the glamour, the allure, the prospect of rubbing elbows with the rich and famous on a weekly basis. Come on, be honest: Isn’t that true?
- Greeting King Hussein of Jordan and his wife Noor in Lanzarote
- Drinking a beer and talking about football with Pierce Brosnan in a Jamaican beach
- Serving tea in bed to the most stunning Miss Italy ever in an undisclosed location…
These are the kind of experiences you can live in our environment if you stick long enough. All true, by the way, and I’ve got quite a few more stories like that, but you wouldn’t believe me.
Most people are in the industry for the fascination, the travelling eagerness, the international ethos. How can we expect them to behave like scientists when checking company’s performance and – more to the point- to make critical business decisions? In the travel industry, it is increasingly challenging to find individuals with a blend of business acumen, methodological expertise, and mathematical/statistical aptitudes. If you’re intrigued by the article’s title, chances are you fall into this category – congratulations! It’s likely you’ve been pondering how to establish and sustain a data-driven culture in your organization.
Before offering some tips, let’s address the three most significant roadblocks you’ll encounter.
It takes time
Half a year, at the very least. For all kinds of companies, adopting a data-driven culture takes time.
- With accessible analytics tools these days, it’s vital to move beyond spreadsheets… and unused reports and dashboards.
- Insights must drive action! they need to trigger action for real progress and growth, instead of relying on hunches.
- Expect a learning phase, but soon, users will see tangible benefits. Everyone will start having a data-dependent mindset, and positive financial impact will be evident.
You’ll make enemies
You’re bound to encounter resistance; people are generally averse to change. The challenge is breaking free from the comfort zone and outdated strategies. The transition to a data-driven culture faces its highest barrier here. Fear of the unknown intensifies the resistance, with concerns about job security and a shift towards a more technical environment. When you disrupt established procedures, expect opposition and, at times, hostility. Some may even perceive you as the enemy, especially those whose subpar performance is exposed by data analysis. Face the potential hate wave as an inevitable part of the process. In the worst-case scenario, if key decision-makers exhibit poor performance, diplomatically addressing the issues is a nightmare .What if data clearly shows their hunch-based decisions are damaging the company? Well, my friend, you have a very sensible diplomacy task ahead…
Data collection and processing = not easy
The bigger your company, the harder it will be to organize, collect, store and process amounts of data that may become humongous. Even for a tiny DMC or family-owned hotel with only a booking engine and an PMS or ERP. I could write a whole series of articles on this subject, based only on my superficial knowledge of it! At the most basic level, data processing requires expert intervention to set-up a scalable system (because you’re doing this to grow, right?) As well a monetary investment proportional to the project’s scope. People love answers from data but hate the hassle of gathering, cleaning, and preparing it. A well-set-up system tackles this nuisance once, allowing you to almost forget about it. At least for a while, until your growing pains force an update.
Here’s the good news
Timelines, rooted bad habits and technical matters aside, the benefits from adopting a data-driven culture company-wide are absolutely worth the wait and the struggle. I suspect you know them already very well. It’s scientifically proven (from financial as well as fiscal publicly available information) that companies operating under a data-driven culture boast lower overheads and diminished risks from decision making, thus consistently increasing profits. Google it if you don’t believe my statement!
The real good news here is that, although it takes some sort of scientific approach to embrace a data-driven culture, it can be attained with reasonable effort, even in the glamour-ridden travel industry.
Practical advice
Each company, each vertical would employ different methods and tools, there is no one-fits-all model. However, there are a few guidelines to create and embrace a data-driven culture within a travel (or any other) organization.
One step at a time!
Start with one area or department critical to the company’s performance. Or with a simple KPI exchange between departments, to find common ground and avoiding fault-searching and finger pointing among stakeholders.
Pose a business challenge!
Establish that analytics implementation should bring a 5% revenue improvement by year’s end. It’s a reasonable objective (and realistic, I should add). However, instead of just pursuing objectives, try checking “what-if” scenarios or run simulations based on the predictions bought by data.
Measure!
The point in collecting data is to measure parameters, to experiment and predict, to answer business questions. Not everything should or can be measured, though. Rather opt for “outcome-based” performance measures to begin with, the so called KPIs… Looking to maximize analytics ROI, focusing on KPI metrics is paramount, although it is a good idea to collect ALL possible data. You never know what might be valuable to measure in the future! And I’m not referring only to quantifiable stuff, also qualitative measures should be accumulated. For instance, if you want to record certain predictions and have no numbers, use “low/medium/high probability”: better to have an approximation than not collecting data at all.
Experiment and Govern!
To take data-driven decisions, you have to blindly trust the quality of your measures. If the prep was done correctly you shouldn’t have to worry about it, right? Not so: always check for outliers, question everything and test alternatives. In short: act as a scientist. Before adopting a data driven-culture, everyone must absorbe at least some data literacy >>. Establish what is a success beforehand, try something, measure its results, home in on the lessons learnt, rinse and repeat. This is especially true to verify predictions’ accuracy!
No experiment is a failure. Instead, it’s an opportunity for valuable lessons, amusement, and discovering new possibilities. Engaging staff in data-driven tasks not only makes their jobs easier, it also brings a sense of fun and competition, creating a motivated and efficient workplace.
Fancify!
Data and related activities are naturally boring for our flamboyant travel execs: ditch tables and spreadsheets, give them elegant flashy dashboards to play around, to easily and immediately visualize whatever data comparison, aggregation or cross-analysis they might need on their daily or monthly basis. Insights can be conveyed into images, or even whole stories, which can be presented with (or through) emotions. At the end of the day, people base their decisions on their feelings: if after having a go at the evidence brought by data they still choose to follow their instinct, it’s their prerogative. Beware of the HiPPO effect >>, though!
Share! Every organization tends to compartmentalize information in silos (in the travel industry, even more so), and that’s something to get rid of. A good idea for starters would be to run bi-weekly or monthly meetings in which all areas or departments exchange a general vision of their KPIs, their experiments results. The long-term objective will be to have a common repository of insights company-wide, so everyone can verify or cross-analyze their datasets against the big picture (company’s general performance). Perhaps the financials officer can discover a way to improve operational aspects… or vice versa!
Commit! There’s no turning back, burn your Excel ships. Make it abundantly clear to everybody that from now on, every decision, every course of action, must be backed up by data. Psychology of resistance is really hard to eradicate, more so in large companies, but if you are the decision-maker you’d better start educating by example and acting based on what data brought forward. If you’re just the main analyst, your superiors must accept that the truth is not whatever their judgement says: truth lies in experiments results (or very close to them).
A few final pointers
If you’re overwhelmed by a mountain of data and uncertain where to begin, consider BIFLIX. The subscription offering includes consultancy for small projects. We assist in establishing your data infrastructure, developing a long-term data strategy, and providing essential training for you and your staff to interpret and act on analytics results.
Finding dedicated data experts for long-term employment is challenging, especially given the nature of millennials and the probable lack of constant demand for a full-time team, unless you’re like TUI or Hotelbeds. For small to medium-sized businesses, fostering a data-driven culture among existing and new staff is key. When system updates are required, specialized third-party assistance can be enlisted, paying only for the specific project. Unless you opt for BIFLIX, eliminating scalability worries.
If convincing staff or leaders of the advantages of adopting a data-driven culture is challenging, showcase the financial benefits it brings to the company, investors, and clients. A fundamental task of analytics is “data mining”. Know why? They’re digging for GOLD, not for the whitened bones of the “this is the way we’ve always done it” extinct defenders. Allow me a cliché here: data is the new oil.
In fact, with no data-driven culture in place, it would be impossible to implement revenue management strategies >>, dynamic pricing >>, etc. Like it or not, it’s a question of survival in today’s harsh competitive environment.
Finally, always keep in mind that data drives no company: people does. Machines and artificial intelligence can feed on data to help see the big picture, check the company’s health and predict outcomes, but ultimately the decision lies on your lap (or your boss’).
How do I know all this?
Because I tried and FAILED, again and again. I studied dozens of data-driven companies (travel related or not) and attempted to implement some sort of data-driven culture in several types and sizes of operators and hotels for years, failing miserably until I started to learn from my mistakes. Maybe I was ahead of my time, most probably I am a slow learner. But to my meagre satisfaction, thanks surely to buzzword spreading, I’m noticing more and more interest in the travel arena towards data monetization. About time!
Did you try all this in your organization? Are you planning to do it soon? Drop me a line, I’d love to share experiences
Thanks for reading!
Marcello Bresin
