In many sports, there’s a factor known as “DEGREE OF DIFFICULTY.”
For example, in springboard diving, a “3-meter forward dive with a tuck” has a degree of difﬁculty of 1.4. Judges rate dives based on four categories: approach, take-off, execution, and entry, and multiply by the degree of difﬁculty to arrive at the ﬁnal score for the dive. In other words, some dives are easier than others and rewarded accordingly.
It’s similar to today’s business executives trying to optimize business performance with data. Some steps are more difﬁcult than others. Let’s look at some examples.
Approach: What? Where? How?
You may not really know what data exists, where it is stored, or have the technical know-how to get it all together for use and analysis. That’s the starting point for successfully getting insights from your data—but it’s only the starting point.
Degree of difficulty to solve: 5 out of 10
Take Off: Analyzing the Data
If you can get past that ﬁrst barrier and locate what you have, where it is, and how to pull it together, then how do you analyze all the data? It’s not simple. You’re likely dealing with multiple types of data: structured, unstructured, front ofﬁce, back ofﬁce, marketing systems, interaction systems, social media, and the list goes on. There’s so much data that even the clear signals can actually look like noise.
If you can get past that barrier of ﬁguring out your data, the next challenge is determining what do you actually need to know? Besides intuition, experience, current data set of reports, advisors, competitive information, Google searches—and maybe a dart board—how do you know you’re getting the highest caliber information and intelligence and removing all the noise that doesn’t matter?
You need to know what you need know before you start asking questions and performing the analysis. To be successful, insights programs need to follow design thinking principles, otherwise, all you get is noise, false ﬂags, and useless detail.
Degree of difﬁculty to solve: 7 out of 10
Once you’ve determined what you need to know, the next step is using all that data to make the best possible decisions. Intelligence without action is a total waste of time, and actions are not always completely obvious, particularly today when there’s so many choices.
How do you leverage the data, insights, and intelligence to develop a list of options? How do you combine statistical analysis in prescriptive analytics and your experience and intuition to make the best possible choice?
And, by the way, time is of the essence! Every business on the face of the planet needs to move fast because their competitors are moving fast, customer expectations are moving fast, technology is moving fast, markets are shifting and shaping fast, regulatory environments are moving fast. So, you need to make decisions quickly from the best possible data with the highest quality signals addressing exactly the right questions.
Degree of difﬁculty to solve: 8 out of 10
Entry: Applying it to Your CX Practice
OK, now you’ve got the ability to make decisions. But more importantly, how do you begin using insights in real time to change customer and business outcomes?
For example, let’s say your customer is in a live interaction with a bot asking a question and the bot dips into the platform, understands who the customer is, their history, their persona, what they are “feeling” now, their sentiment in the past, their past purchases and can predict what they are trying to do now. All of this culminates in a singular response that enables and equips the customer to take the easiest path to resolution, which creates the highest value for the customer and for the enterprise.
Degree of difﬁculty to solve: 9 out of 10
Ultimately, the next and ﬁnal step is to quickly understand and assess whether the changes you are driving in the business are creating the value you expected. This constant feedback loop is critical, because without it, you won’t be able to adjust with the scope, scale, and speed that is required to be successful in today’s business environment. It’s essential to measure the right things in the right ways at the right time, and produce future signals that are going to enable you to meaningfully manage the business.
Degree of difﬁculty to solve: 10 out of 10
Diving into Your Data
You don’t want to get this wrong and end up doing a belly ﬂop. Not only is it painful, but you’d be out of the competition.
Whereas diving has it’s scoring steps, at Concentrix, we use a model of:
Or, in short form: Insights to Outcomes.
Is all of this easy? Clearly not. Is it solvable? Deﬁnitely. We’ve built a team of data insight experts that have helped businesses across multiple industries solve exactly this challenge, and do it in manageable chunks. We can help evaluate what data you have, where it’s located, how to evaluate it and turn it into actionable insights, and then measure outcomes and adjust in real time.
Please join our panel discussion “Leveraging Customer Data and Insights to Design, Build, and Run a Winning CX Program” at Execs in the Know’s Customer Response Summit on March 2, 2023 at 2:15pm. I’ll be moderating a panel with CX leaders from United Airlines, Vistra, and iRobot.
I hope to see you there when we discuss how to help you get to a perfect score!
Guest blog post written by Reagan Miller, the Global Vice President of Analytics and Insights at Concentrix. To learn more about this topic and others, visit the events page to check out all of our upcoming events.