How CRM Software Boosts Staff Productivity
- Research shows that nearly one-third of Customer Relationship Management software adopters did not achieve any improvement to staff productivity.
- The top performers cited Artificial Intelligence (AI) as a top contributing factor to labor productivity 3.1X more than the remaining population. AI was the single biggest difference among performance archetypes to impact user productivity.
- The top performers led their CRM implementations with a business sponsor, as compared to an IT executive sponsor, 4.2X more often than the remaining population. This was the single biggest standout variance related to employee productivity.
Research performed for the CRM Benchmark Report identified some significant differences in how the top performers applied this technology to achieve the greatest improvements to labor productivity.
Here's some of the results.
How Does CRM Impact User Productivity?
We first posed a question to understand the impact of Customer Relationship Management software on staff productivity.
That question surfaced two unexpected results. First, 13 percent of respondents reported a "productivity loss" with the adoption of this technology. We know by correlating this answer with another question in the survey that an increase in data entry is the top cited reason for the productivity loss.
It's unclear whether these companies factor in the increased cost of labor with their technology investment. It would seem clearer that when technology increases the top cost category for most companies that the technology is at risk of termination.
Second, when the two categories of 'Productivity Loss' and 'No Improvement' were summed, they totaled 31 percent. It's alarming that nearly one-third of technology adopters do not achieve labor productivity improvements.
Fortunately, two-thirds of respondents did achieve positive results. So, the remaining research results are separated to show what the Best-in-Class performers (i.e., the top 15 percent) did differently than all others.
Technology Driven User Productivity Capabilities
We asked respondents to rank the top system capabilities that most influenced employee productivity. The tabulated results are shown below.
When comparing the Best-in-Class performers to the total population, the data demonstrated more differences than similarities.
In particular, the top performers identified Artificial Intelligence (AI) as a top contributing factor to productivity 3.1X more than the remaining population.
We also asked participants to rank the factors that most challenged employee productivity. Three obstacles stood above all others.
We know from three decades of implementation history that resistance to change is pervasive but can be mitigated with a change management program.
We didn't expect the second most popular response of increased data entry. Supporting comments with the response advised that CRM systems require staff to spend significantly more time entering data to the application. It would seem for these respondents there was a productivity loss from the data entry requirement that was not later recouped with other productivity benefits.
At the other end of the spectrum, the top performers rated increased data entry dead last, thereby suggesting it was not an influencing factor for them.
We asked respondents to identify the top executive sponsor for their implementation. We wanted to know the answer in and of itself. We also wanted to correlate the answer with other labor productivity-related findings.
The data demonstrated that the top performers took a very different approach than the remaining population. The Best-in-Class cohort led their implementation with a business sponsor 4.2X more than the remaining population. This is a very significant variance.
We applied some anecdotal experience to interpret this data. We have been helping clients implement CRM systems for three decades, and it's clear to us and most others with similar experience that IT led deployments have a much higher tendency to focus on technology goals (i.e., get the software operational) while business led deployments focus on business goals (increase sales, customer retention, user productivity, etc.)
It's our opinion that it is unfair to ask IT professionals to lead an implementation program for which they are neither the user nor the beneficiary. IT staff are essential for any technology deployment. But if you expect business benefits, business leaders must step up.
We'll be updating the next version of the questionnaire for this report to drill further into the significant sponsor differences.
Top 5 CRM Productivity Best Practices
Research insights are made actionable with best practices. So now I'll drill down on the top cited technology capabilities to improve user productivity.
Automated Business Processes
The top CRM software capability cited by all respondents to improve user productivity was business process automation. But there's an important caveat here. Bad processes are not helped with good technology.
I think Bill Gates said it well.
User productivity is enabled with technology, but not achieved with technology alone. It's important to streamline and simplify business processes first, and then automate them. Otherwise, you just end up with an automated mess.
When done in the right sequence, automation replaces manual activities, accelerates business process cycles and reduces data-entry related errors. More importantly, increased automation allows staff to spend less time on entering and fixing data, and more time applying that data to better serve customers and make more informed business decisions. Business process design is often the single greatest contribution that will impact staff productivity.
If you are unsure how to improve business processes, I suggest Agile Value Stream mapping as your starting point.
Artificial Intelligence Capabilities
Among respondents that achieved the highest productivity improvements, AI was their number 2 tool.
AI with CRM software is most effectively deployed when specific use cases are configured to drive targeted business outcomes. The below illustration shows several sales-related AI use cases and their relationship to sales outcomes.
AI in a CRM system can predict customer behaviors, recommend offers, content, products or next best actions, forecast which sale opportunities are winnable and which are not, and perform other capabilities just not possible without AI.
Our experience finds that helping clients implement AI within their application shifts the software from a customer data repository to a predictor of customer behaviors, creator of customer insights and facilitator of customer and company objectives.
The User Experience
It wasn't surprising that the CRM user experience ranked in the top 3 factors that drive employee productivity.
That's because a complex or difficult to use application isn't going to achieve user adoption, which is a prerequisite to user productivity. To achieve the highest user adoption, it's helpful to understand the differences between the user interface (UI) and the user experience (UX).
A CRM user interface is like a joke, in that if you have to explain it, it doesn't work.
The UI is focused on simplicity and visual presentation. But the UX goes further and applies consumer technologies to facilitate user journeys, business processes and prioritized use cases.
There are two ways to significantly improve the user experience.
First is applying user-centered design. Most implementations state goals in software terms and not people terms. They apply design to software screens and not user experiences. They emphasize software ascetics over usability. They operate under the premise that if they build it, the users will come. However, three decades of CRM software implementation history suggest otherwise. Prioritizing technology over people has clearly contributed to the staggering and often cited CRM failure rate.
Second, recognize that software publishers such as Microsoft and Salesforce have developed their applications over more than two decades. They have created countless software features, functions and capabilities. And while that's helpful when needed, displaying more capabilities than is needed is unhelpful. It creates clutter, makes screens unnecessarily complex and reduces ease of use.
Application forms and screens should display what’s needed and no more. UX professionals know that removing unnecessary fields, functions and content delivers a cleaner, simpler or more rewarding user experience.
Timely Information Reporting
There are several types of CRM information reporting, including views, lists, packaged reports, predictive analytics and dashboards. But it's that last type that is most associated with improvements to staff productivity.
Dashboards display the most important key performance indicators (KPI) in an easy to consume visual interface. They prioritize role-based information to show what should be done first, and then next, and so on. They identify variances and trouble spots in real-time so that staff can quickly intervene with timely course corrections.
An interesting thing about dashboards is that users spend less time accessing information reporting but leverage more insights to improve their performance. That's the sign of successful reporting. If the information is causing changes to user behavior, it's working.
Push-based Information Delivery
Technology saves employees time when it automatically delivers valuable information that would otherwise require an investigative effort.
Many systems can shift information reporting from pull-based (find it yourself if you have time) to push-based pursuant to information subscriptions or AI recommendations.
Both methods can deliver predefined information to designated resources upon a triggering event. However, AI can add additional business or customer intelligence to make information delivery more dynamic and contextual.
These notifications may include things like resolving revenue leakage, such as sales leads not being followed-up or sale opportunities not being followed-through. Or they may surface business process breakdowns such as a quoting or order entry problem. Or AI may recognize that a high value customer is dissatisfied and at risk of churn. Swift course corrections prevent the loss of short-term and long-term revenue.