Why do Customer-Centric Organizations Fail?

In an earlier post on customer-centricity I had argued that executive reviews rarely go beyond the numbers (revenue, subscribers, traffic, etc.) and fail to capture a more powerful growth engine – our customers. But, what if our strategies are built around customer success, yet the goals are not achieved? 

There could be a multitude of reasons namely, market saturation, competitive pressures, product quality, marketing success, operational effectiveness, etc. While most of the listed here may be in play, in some form or the other, I want to bring our attention to “operational readiness.” 

We can hire the best consultants to design our product, consumer and marketing strategy, but it is our operational readiness that will determine how well we deliver on this strategy. 

Let’s take an example, we have our corporate mandates such as; expand our footprint, diversify our product offerings, increase ARPU, reduce cost, sign a new partnership, etc. We conduct due diligence, come up with a strategy to achieve that objective, and with a fancy deck, will have all the approvals needed for a launch. However, there is often a need for "incremental investments" and a shift from "corporate ways" that are critical for our operations to deliver. 

In my experience at leading new product launches and customer-facing site enhancements, the build phase often springs up unexpected surprises that either cause delays, or force a go-ahead with a compromised product/service features. These could be in the form of systems and process updates (may require capital investments), shift in strategy to offer a "beta" version of the product, shrink the scope of support offered through CRM, etc. As a P&L manager, it is important to highlight the larger gains and keep the project ROI positive and within acceptable range.

A well thought out and “realistic” implementation plan should be integral to the strategy deck for a new initiative. 

So, don’t underestimate the value of conducting due diligence and investments around building operational capabilities to meet the strategic goals. That is one activity which will significantly impact the success of; new product launch, analytics integration, a website redesign, and systems upgrade, etc.  

The bottom-line is that the cost of an unsatisfied customer is far too high to under-estimate the costs of poor delivery. 

In one of my client engagements, I had to re-evaluate the product features and SLAs that were agreed upon with the partner, as these were leading to customer complaints and unacceptable levels of churn. Part of the strategic redo included a better communication collateral for sales and marketing channels. The compromises made during the launch to meet the deadlines would come back to bite so quickly - no one had imagined! 

Are You Ready For the Anlaytics Fast-Lane?

Data and analytics are everywhere, with numerous examples of how the right analysis yields significant lifts in marketing or operational efficiencies. The returns are, without doubt, measurable and worth the investment. However, a word of caution for the leaders – don’t be swayed by case studies and peer recommendations, or assume that employing an analytics firm will yield similar results for your business. Being ready to utilize the feedback in a timely manner, with a clear implementation plan, is equally critical to realizing the ROI on your analytics investment. Here are a few questions to ask yourself, before embarking on an analytics project.

1. What is the problem statement? Be clear with what question you need answered. It could be; defining the target audience for your product or/service, understanding customer engagement with your product, improving acquisition effectiveness with better offers, identifying churn propensity by customer cohorts, etc. The key is to explicitly state the goal, stay focused and avoid the “noise.” Defining a clear problem statement upfront is crucial to staying focused and not be distracted by a lot "interesting" findings that are bound to pop-up.
2. Do you have the right data set? Work with your analytics and IT experts to identify the right metrics needed to answer the above questions. A third party perspective is always recommended in such instances, since it helps question the status quo and is not bound by what is familiar. Start as comprehensive as possible, since analytical modeling often throws new data dependencies that may not have been obvious. A holistic view of data points available from the data warehouse go a long way in defining the problem statement.
3. Is the organization ready to ingest the analysis? The best time to use the analysis is “now.” I have often contended that analysis based on historical data is like playing catch-up. But, with predictive modeling we can project certain behaviors with a fair degree of certainty. The imperative hence is, that an organization has the operational capability to act quickly on the recommendations (marketing & sales changes, product updates, online experience edits, etc.). Invest in the back-end systems that can adapt and learn from the new programs, or else, run the risk of being obsolete.
4. Do you have dedicated personnel to guide the process? This is the most important determinant of success, and perhaps the most overlooked as well. A well defined problem statement, predictive analytical models and process efficiency cannot be achieved unless we have the right analytical minds leading and nurturing the program. As an organization, we need to recognize the need for analytics leader who has the resources and can rally the operational teams to achieve the desired outcomes. The ROI of analytical projects depends on this critical investment, just as it does on problem statement and analytical modeling.

Analytics and data modeling empower the businesses, and to stay competitive, businesses need to equally weigh continuous innovation and implementation. Rapid deployment is as critical for success, as is harnessing and modeling business metrics!