5 Top Reasons Analytics Adoption Fails

Almost every organization has adopted, or attempted to adopt, analytics. Data and analytics are critical to almost every business decision that is made. However, those decisions are not always being made with the right data and aren’t necessarily focused on solving the right business problems. As organizations face these challenges, progress on their analytics initiatives sometimes slows down or even fails. Below are some of the top reasons for failure:

1) Not truly understanding the business value.

I have personally worked with a number of clients that went in headfirst and started building dashboards from what they thought was their most valuable and insightful data within the company. The dashboards looked amazing - numbers, bars and lines filled the screen – but never answered any of the underlying business questions. Low and behold, what they actually had accomplished was “digital reporting”, and not analytics at all. Analytics is about improving decision making, creating more effective marketing, providing better customer service and streamlining operations. Analytics requires a top-down approach - developing the business questions and KPI’s while finding the supporting data sources to answer these questions. Most important and least thought about is ensuring that questions and answers are “actionable”. If you cannot align the business questions and KPI’s to some meaningful action, there is no point, thus no value.

2) Believing analytics are overrated; and Excel has you covered.

Excel has certainly stood the test of time, and is one of the most powerful tools within practically every business enterprise. Businesses need to use Excel for what it is meant for and capable of doing – organizing and manipulating numbers and data. It's an amazingly flexible program to find answers to logic-based questions. It allows business users to manipulate and report on data. However, with all due respect, it lacks the ability to provide insight into large datasets and perform advanced analytics techniques. Leveraging the power of analytics and quickly finding actionable insights within a business is essential in today’s fast paced and ever-changing economy. You need to be able to marry-up financial data, with customer, sales, product, and even social listening data to begin developing the necessary picture for effective and efficient business decisions within your organization. As a small business, you may not notice a sudden 12% increase in sales on the 3rd Thursday of every month, but your payment system might. That seemingly small increase in sales on that one day a month might go unnoticed for some time, but the results can have a dramatic snowball effect. May even lead to shortages down the road, magnified across multiple stores or outlets. This is the power of analytics that can make a difference.

3) Trying a small analytics project, and having it fail miserably.

Every analytics demo I’ve seen looks so easy and simple. Companies talk about creating actionable analytics with data from across the organization and the most state of the art visualization tools. And while you obviously need the data and a good visualization tool, there is more to it than that. You need to develop a roadmap, to know where you are going, and what to do when you get there. It’s no different than when you are going on a vacation. Being able to expect and address the obstacles along the way is essential. The data is like an uncut diamond, relatively worthless until it is thoroughly examined, sized, and cut. Your data needs the same approach. The data has to be properly prepared for visualization – normalized, cleaned, completed and transformed. Eliminating duplicates, blank records, nulls, addressing missing fields, values etc. is all part of this task. Next, and critically important, being able to install the “plumbing”. Implementing security, data flow, timing, updates and being device aware. Simply stated, you need to be able to deliver the right information, to the right people, at the right time, on the right device.

4) Not knowing where and how to start.

This is one of the more common adoption challenges across organizations. Quite frankly, there is a lot to think about and cover at the start, such as: Selecting the right “first” project, toolsets, resources, skill sets, data storage, ETL processes, security, data flow, scalability, and cost. Getting your arms around each of these areas can be challenging in and of itself, and tackling the entire list can be overwhelming. This is where experience and practical knowledge can be instrumental and get your organization off on the right foot. Avoiding common mistakes, deploying best practices and showing an immediate ROI can go a long way to deploying a successful analytics initiative.

5) Having issues with data ownership.

Almost every enterprise analytics project I see taking place runs into the issue of data ownership.  As an example, many of the projects I see being executed include data that lives in multiple places with many owners, call centers, customer success systems, CRM, ERP, Systems of Records, to name a few.  Each data set has different owners, different security and PII requirements, and trying to get access/agreement tends to be the long pole in each of these engagements.  More importantly there often isn’t a single sponsor who can make timely decisions, so committee decisions rule the day.  There is a need for organizational clarity that may include a Chief Data Officer, Chief AI Officer or a data center of excellence that can really accelerate analytics projects to success.

6) Lack of buy-in across the organization.

Related to, but slightly different from data ownership, is ensuring buy-in across the organization on the importance of analytics. While business users typically see the value and need for analyzing data to drive their decision making, there are many others within the organization that are required to make it happen. IT teams are critical to ensuring data availability and security and can delay and obstruct progress. C-level executives need to embrace the adoption of new technologies and techniques and push the organization to expand their current thinking on how data can be used throughout the organization.

While there are a number of reasons why analytics adoption stalls throughout the enterprise organization, this does not mean a company cannot be successful. Each of these pitfalls can be avoided through proper planning, education, and leadership. Organizations should follow the AAA plan of ensuring analytics adoption by making sure their data is:

Accurate: Validate the data that is being utilized is the most up-to-date and correct data. Nothing will deter usage of analytics more than someone finding inaccuracies in the reporting.

Available: The best ability is availability. This can be applied to data, in that your analytics will only be valuable if the data you need is available when and how your business users need to consume it.

Actionable: Ensure stakeholder adoption by including them in the process. Identify and understand the challenges various business units face, and make sure the data that is being analyzed and reported on will help solve the identified business challenges.

As organizations adopt the AAAs of analytics they will be well positioned for success and demonstrating business value.

The value of analytics is fairly easy to realize when implemented correctly. As businesses start to see increased operational efficiency, more successful marketing campaigns, improved customer retention, and many other benefits, adoption will continue to improve and analytics will soon be driving the decision making of the entire organization.