So here we are, finally at number five on the list of Top 5 trends in 2013 for Customer Service. It has taken me a while for this to wrap up, but this will be the final topic in the series that I will explore, Analytics. There is a lot to say on this topic, so strap in for a few minutes while I give my view of the world and what I am seeing in my work in the field.
My deep interest in the idea of data and Analytics actually started a few years back now, actually more than 10 years ago now when I took a break from working and went back to school, in Sweden! Back in 2002, my buddy and I were very interested in this new space that was emerging in the US and in other parts of the world called BioInformatics. It was described at the time as Biology meets Computer Science meets Stats. A pretty easy way to describe it back then to people, but they still just gave you a blank look and thought you were over the top smart. If they only knew me they would know that that was far from the case. Computer Science and Stats were never my strong suit in college, in fact the only C I got in college was in my Intro To Computer Science class. Still burns me to this day.....
Anyway, the point is that for many years now, we have been using the idea of data or Analytics to understand more about the world around us. And in particular, Financial Services and Life Sciences companies have been using data and Analytics tools for a number of years to pick up on business trends, spot fraud or to find the needle drug in the haystack that a pharma company would spend $500 million to develop and bring to market.
Fast forward to 2010 or so and the term Big Data entered our lexicon in a big way. Everyone seems to have an answer for Big Data, but the challenge is that no one ever seems to be using the same definition. And then you layer in industry jargon or department specific needs and you end up with a proliferation of companies that all say they do the same thing. That is far from the truth and this post is meant to call out a few questions that you should be asking of yourself and companies before you get too far down the road with investing in Big Data. These questions are not going to be the IT based questions that always come up with Big Data like speed, storage capacity, variability etc. We will assume for the sake of this post that IT has a good handle on all of those important pieces. In this post, we will just focus on the business side.
In the vendor world, there are a number of different types of companies that offer Analytics solutions for service organizations. There are Business Intelligence companies, Customer Experience Analytics companies, Analytics companies, Text Analytics companies, Voice Analytics companies and a whole host of companies that have niche software products that bolt on some form of Analytics like survey companies or Voice of the Customer companies.
Thus, you see one of the biggest challenges of the new world we live in, the increasingly complicated and siloed world of data collection. I remember sitting in front of a VP of Marketing at a Telco a year or so back and she looked at me and said, "I wish that someone would help me bring all of that data together into one spot so I could analyze it." She is spot on and this is the same feeling that many share today across all industries. There are just so many collection points and not one good way for business lines to aggregate all that data into a useable format. This is the first challenge and question that I want to call out to leaders in customer service. How are you thinking about aggregating the data you are collecting to then analyze later?
The second big challenge that many people are dealing with in service orgs today is, how do I work with IT to get the data I want, in the format I want, in a timely fashion. For years, IT has had a strangle hold on the data in a company and has had to set up teams of people to help translate the needs of the business into searches or what are typically called queries, that gets the data that the business people need. Many of the companies in the Analytics space today are making things easier by developing interfaces that actually allow business users/analysts to get the data they need. But most of this is still an effort that needs to be led by a person with special training in the tool and there are not any tools that really cut across the landscape of the silos of data collection. So you still end up needing to learn the Analytics packages from each vendor to bring together the data in a way that makes sense. This interface proliferation and training naturally then cuts down on the numbers and types of people that have access to data to find information. Just like anything else, if I am a busy person in my company, going from meeting to meeting all day long, I am not going to take the time to sit in a training class and learn a new interface to pull info from. It has to be dead simple. So simple that I don't need training. That is when people will actually use it in droves. So before you invest in any Analytics package, ask yourself and your team, is this only going to add another interface to our lives to pull data from?
The third biggest challenge I see all the time and to me the most important, is the idea that no matter how much data you have, it is becoming less important to just be able to run reports easier. It is less important to have a new UI that lets business people create their own dashboards. What is really the next wave of Analytics is the question "What am I not seeing?". Today companies are really good at pulling up dashboards, building reports and finding information when they know they have a problem. VPs of Marketing or Sales are really good at telling the Analytics team or their Ops teams to come up with a report or a dashboard when things are going wrong and they need to tell the CEO why. Orgs are really good at the firedrill mentality. But what they are not generally good at is asking questions of their data to find patterns or correlations that they never knew existed before. This type of work is typically only done in very very large companies with incredibly advanced teams of PhDs working on regression analysis with large, complex statistical analytics packages. Not the norm for most companies and certainly not the norm for most customer service teams. But this is where things are going. So the question needs to be from you the buyer to the vendor of any Analytics system, "How are you going to help me find the things I don't know?".
There are literally dozens upon dozens of new Big Data companies that are coming into the market. It seems like a day does not go by where you don't see a new name pop up on the Start Up news sites. But, before you go investing in point silo solutions from any new little vendor out there for a specific need. Make sure you ask yourself and these vendors the three questions posed above. It will save you time, money and a lot of headaches down the road!
