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By Walter Scott
Devo CEO Walter Scott writes about using data to manage companies for excellence in operations, financial results, and employee engagement.
Digital transformation is increasing the machine data available for operational analytics, empowering organizations to improve every line of business. For organizations to grow along with this onslaught of data, they must have a 360-degree view of what they’re collecting and use it as a guide to how to do business.
Getting control of data to make business decisions is crucial to competing. When companies start looking at the data they collect, they use it to validate what they feel. But then they stop looking at data and go by feel. This is a problem for companies with data science models that have not evolved, or where the strategic value of data is not driven by the C-suite. In other words, data is available only in silos, so no one has the big picture.
Data silos are a serious business problem. We gather machine data in one place, security data in another, customer experience and support data in another — the list goes on. This structure may make sense at a departmental level, but it prevents collaboration necessary to ensure competitiveness. Companies need an operational data layer that is core to business processes and supports data sharing.
Let’s use my experience with a sportswear brand I’ve worn for years to demonstrate the impact of lost opportunities to learn from sales data. We’ll call the company Steve’s Sportswear.
Consumers Signal Discontent On Multiple Channels
Brands need to understand all data points and sources that signal consumer discontent. Twitter and Facebook are early-warning systems for user unhappiness. But is this data sitting only with marketing? If so, it’s a missed opportunity for the company.
Brands also need to pay attention to transactional data from finance. They need to monitor items left in a web shopping cart. They need to monitor chatbot data to understand service issues. Steve’s Sportswear knows what I purchased, and they’re missing an opportunity to reach out to say, “How do you like the Classic Pants you bought? Have you tried our new polo shirt, made from a similar fabric?” One-size-fits-all consumer marketing is dead — brands need to tailor interactions to the customer.
Steve’s Sportswear also knows I order a certain T-shirt regularly. The last time I attempted to buy some, they were out of stock. It would have been easy to let me know when they were back in stock. But I got no feedback — another missed opportunity. At this point, I’m looking for a new brand, and Steve’s Sportswear is losing someone who spends thousands of dollars a year with them. They’re not watching what the data is telling them: I’m a high-value customer. A brand-loyal consumer has a significant drag effect. Do they know that my wife buys items for me and my son, as well as herself? Do they think she is one customer or three customers?
Steve’s Sportswear’s sales team should develop programs to look at data from high-volume consumers to ensure stickiness with profitable, loyal customers.
Ignoring Data = Lost Opportunities
Steve’s Sportswear delivers everything I order by mail in a signature bag. Recently, I noticed they weren’t including the bags anymore. Is it worth the $1 they save not sending my $58 T-shirt in a bag? Steve’s Sportswear tracks everything about every sale and knows how much I spend. They should at least ask whether or not I’d like a bag with my order.
The Problem With Silos
I share this experience as an example of how a company can increase a customer’s lifetime value if they pay attention to data. Between transactional, proximity and survey data, a company has a 360-degree view of customers. It’s not hard for a CIO to make sense of the data being collected if they’re keeping an eye on the big picture.
One problem with collecting data is that who has access to it can become political, reinforcing silos. If I’m the CEO and I’m unhappy with sales, I go to the sales team to understand, but they may blame marketing. Each team uses its own data because they want to preserve the dataset that supports their point of view. In this pattern of behavior, if you control your own data, no one can hold you accountable. Silos defeat collaboration and stymie value creation.
Any time data is touched by a human, objectivity decreases. Machine data is objective. It provides a single version of the truth — one the entire enterprise should share. But it’s impossible to have one version of the truth if the data is in silos.
Having one set of operational data gives a leader insight. A CEO can tell if a customer is thinking about canceling by looking at data as wide-ranging as how many support tickets are filed at once, how many doc pages are viewed and if they unsubscribed from the company’s email. While these are separate data sources, when viewed together, they point to one likely outcome. Until data is collected and analyzed across the enterprise, it’s not useful.
How To Build A Data Strategy
To get a handle on the data you’ve collected and make it useful, identify where silos exist. Everyone in the C-Suite needs to agree. Identify trackable interaction points and align them with key performance indicators. This data is broad-ranging, from what is in your transactional databases to network traffic, application logs and website logs. Security, physical and digital, needs to be analyzed. Each data point in its own silo is valuable, but combine them and you’ve compounded the value of your data.
Breaking down data silos is more than an IT task — it’s an exercise in building a more collaborative culture. Take the first step and bring your executive team together and get them to commit to sharing data. Look for a platform that gives visibility into all your organization’s data, and empower your team by making them stakeholders. Then, take the benefits of the 360-degree view of your business and build stronger relationships with your customers. Trust me: Customers will notice and reward you. Looking at you, Steve’s Sportswear.
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