First, there is an important distinction between believability and accuracy. We assume the data is accurate which means free from error. Some sources are more credible than others. Over time, people tend to learn which sources can be trusted (for specific purposes) and which they cannot. Do the data sources you currently have create situational awareness for the communities you serve?
Then there is personal accuracy. At Zartico, we have created a process such that each of us double check each other’s work for accuracy and logic because there is no faster way to diminish credibility than to present inaccurate information. We encourage each other to ask ourselves the following questions:
We don’t care who you are or how good you are at your job, having a confidant to validate important work and serve as a sounding board is critical.
The second key to believability is specificity. Consider this example: customer service people come and say “everyone is complaining’ or “every call is being dropped”. As a leader, you are likely to find this approach entirely off-putting because it is nearly impossible that everyone was complaining. Rather, it is important to be specific when specifics mattered. It is far easier to believe the data when you say that “68% of our consumers are complaining due to wait times greater than two minutes”. This is actionable data; it is scientific with context.
Specificity is also being exact… “61%“of people reported satisfaction is more believable than “about 65%” or “There are three steps we can take” is more believable than “There are several things we can do.” If you know the exact number then you are probably going to be looked upon as someone who has earned the right to be considered a credible source of information.
A study reported in the Harvard Business Review said that by including a graph increased its perceived effectiveness by as much as 23%. In another study referenced in the article, 96.55% of those who saw the graph believed the medication would reduce illness, versus 67.74% of those who did not see the graph. The main takeaway is that graphs and clear visualizations help audience members understand more quickly data that is presented, not to mention the scientific halo of graphs. So, like it or not, visual illustration of data makes it more believable.
Transparency is another key element. Anyone who deals in forecasting, model building, AI or any level of data analytics knows that the truth is in the assumptions. For many of us who are researchers or live in the world of data understand and appreciate not only the power of market research but that data can be manipulated based on your assumptions and techniques. Therefore, if you want to be believable, then the methodologies need to be transparent and communicated. At Zartico, we prefer to put our assumptions front and center so that people can see where we have taken the liberty of making an assumption.
Sharing methodology (the inputs and assumptions) is another critical step to earning credibility. Consider including your key stakeholders into your data conversations where they have the opportunity to contribute to key decisions and understand how you are utilizing scientific methods to measure tourism constructs. Everyone knows that the devil is in the assumptions so make these known. This creates transparency. The more understanding your audience has of how the answer or recommendation was calculated, the more believable. Tourism, more than ever, lives in a glass house and transparency is paramount.
The world is changing at breakneck speed. Data needs to be real time and delivered at high frequency in order to make decisions. No longer is the once a year or even twice a year survey fast enough to understand what is happening in your market.
If you are a leader within a DMO, you need to make daily decisions on both leading and lagging indicators. You need data that tells the story of past, present and future. The accessibility of real-time data that can be analyzed at a high frequency also helps with believability. It provides situational awareness. When we look at data, we ask the following questions:
The efficiency of an organization can be measured by the amount of time it takes to turn data into insights, and insights into action. Many businesses create a real time company-wide dashboard that shows the team where they are winning and losing. The quicker we can identify a problem, the faster we solve the problem and move forward.
This is true for business strategy. Missions and values stay the same but strategy, the HOW we do something, needs to change with the environment. Real time data is paramount to making this happen. Certainly there is a place for a comprehensive, yearlong study of certain aspects of your plan but the small micro decisions are what keep our businesses nimble. Some of the high-frequency data we have used at Zartico include UberMedia geolocation data where the lag can be as short as five days and online surveys performed weekly asking 1-3 questions to look at trends.
We often think about Stephen Covey’s statement “If the ladder is not leaning against the right wall, every step we take just gets us to the wrong place faster.”
Ultimately, the alchemy happens when we triangulate our data analysis, by overlaying other data sources including market dynamics and, yes, intuition. By overlaying multiple data sources, DMOs now have the opportunity to anticipate the “second level” questions and make them easier to answer. As an example, if there is a spike in visitation to a given POI, or a surge in web traffic, we’ve tried to put the answers to the drivers of those changes only one-click away so you can answer the question “why”?
Technology now affords us the ability to run thousands of queries across multiple sets of data to see if they are all telling the same story. If two strands of data are challenging a strand that is commonly trusted, then it alerts us to dig deeper and find out why. Through technology, we can now conduct multi-channel verification of outcomes before they are presented to your State, county, or community.
Most of us have been in our profession long enough to value our “gut” intuition and this cannot be understated. The power of data is truly unleashed when it is combined with analysis and real world experience. Connecting the dots of what we see, know and feel is the mark of a seasoned leader.
Data without narrative is just that, facts and figures. But data with a story inspires action. One of the questions we need to constantly ask ourselves is “what is the insight and what is the story?” If we can’t tell the data in a story, it is useless because without a story, we will lose the audience on the action.
Right now in tourism, the story is jobs, consumer confidence and well-being of our communities. How do we as an industry take the data and turn it into a narrative of the support our industry needs that results in policy change. Data can support making the story personal. Humanize. Tell a story that brings in main street business. Show how data is positively affecting the community. This is why Presidents invite people to the "State of the Union" address. These people are voters and usually they are part of the story. Storytelling is a lifelong journey of which we are still on but here are some of our favorite resources http://www.richardgreene.org/ but really this is another blog entirely.
This is probably the hardest lesson. We all want to know every stat and figure and have probably created 100 page appendices “just in case” someone asked that obscure question. Then, even though you had prepared for what you thought was every possible question, someone would ask you something you did not know. If you are like us, you might venture to make your best estimate and in fact be wrong. But it is likely that the best answer in those moments was “I don’t know but I will look it up and get back to you.” It was far more effective because it inadvertently let people know that you only speak to something you know is accurate…which in turn makes it believable.