Monthly Archives: February 2015

8 Tips to Get Your Team Using CRM in 2015 by Michael Hanna

A CRM implementation is more of a cultural change than a technological change. That’s because adopting a new system requires changing habits, and changing habits is hard. It’s hard for those who want to change, let alone those who do not.

Most people demand change, but resist it when it comes. Resistance to change is natural, so it’s crucial to help CRM users through the process of embracing change. When it comes to CRM adoption, users need your help, they need your reinforcement, and they
need that culture of accountability.

Here are four practical, actionable steps before, during and after the CRM launch.

1. Be Aware of Data Integrity

System-to-system consistency, or the integration of multiple systems, is crucial for a strong cadence and user adoption. If you’re migrating from one CRM to another, or merging CRMs, or changing CRM providers, ensuring the data is successfully merged and consistent is crucial to having data integrity. Without data integrity, this process often results in duplicate data, unstandardized or inconsistent data, and missing data. Preparing for these data mishaps in advance, as well as having tools in place to clean and prevent them from happening, will ensure CRM system integrity.

2. Be Clear About the Goal of CRM

Your CRM users are looking for the why behind the CRM system. If you’re not sharing this insight, you’re wasting your CRM investment because users simply won’t adopt it. Deliver clear rationale and a cause for your CRM. As a sales example, CRM gives users visibility that enables continuous sales improvement.

3. Hold CRM Users Accountable

It’s important to empower your CRM users, and CRM adoption should focus on that. However, empowerment without ownership is going to lead to neglect. You can give your users the most pristine, high-end CRM, but if they don’t care, they’re not going to use it. Establish the CRM users as the owners of the CRM, and then, in the context of ownership, empower them to use it. Otherwise, they’ll be negligent and passive.

4. Manage Detractors

If you’ve got ten sales reps using your new CRM, and eight of them are adopting it beautifully while two of them are struggling, you must work hard to get the two back on track. Stay strong and don’t lower your standard, or else the other eight are going to start to slack as well. By not diminishing your expectations, holding users accountable, and providing help and assistance, all 10 sales reps will be completely on board.

5. Demonstrate Real Results

Look for opportunities to showcase the relationship between CRM adoption and the positive sales performance that results from it. Explicitly call these results out when they happen. Here are three examples of these opportunities.

Sales reps quickly follow up on leads delivered in real-time via the CRM resulting in higher lead conversion. Call it out!

6. Provide Ongoing Support

Be extremely responsive to the sales reps’ questions and challenges, and try to support them in real-time. Refer them to your documentation and add their questions to your feedback list if you haven’t addressed it in your documentation.

7. Be Mobile

Reps do not want to have to go back to their desk and spend an hour everyday updating a CRM. This creates detractors. Allow users to update the CRM system in real-time, including while they’re in transit, when they’re coming out of a meeting, and so on. Mobile CRM enables users to access their CRM without pulling out a laptop and connecting to WiFi. Mobile deployment is a critical part of CRM user adoption.

8. Keep the User in Mind

Don’t introduce so much change that users can’t swallow it, and they can’t adopt it even if they wanted to. Pushing too hard or too much will deepen the mindset of existing detractors and create new ones. Your CRM success will only be as strong as the rate at which it can be adopted, not the rate at which it can be implemented.

The CRM adoption process is a journey, not a destination. When asked if the CRM adoption process is ever done, the answer is simply, “No, it’s not.”


Read more at http://www.business2community.com/customer-experience/8-tips-get-team-using-crm-2015-01135865#roodxkOyQwshISmO.99

6 Trends Shaping Government/Citizen Relationships by Timothy McCormick

I found Salesforce Timothy McCormick’s blog post on the citizen engagement initiatives within the City of Philadelphia, including the launch of the new 311 non emergency Customer Relationship Management (CRM) software, was on point as it pertains to the growth of excellence citizen engagement and experience in the public sector.

Below is an excerpt from the blog and link to the entire blog post for your review.

Citizen engagement is less than desirable–with long lines, lots of paperwork, and the confusion of a bureaucracy make it hard for citizens to access the right information. How often are citizens reporting issues vs. commenting (or complaining) on a soap box over social? How many elected positions ran with uncontested candidates in your last election?

Timely responses. How many times have you thought, “What more can we do to make this move faster? Why does progress on XYZ project seem to move so slow compared to everything else in life? How can we possibly do more with stricter budget and fewer resources all around?” Not only does this make it hard to motivate teams, but also it causes citizens to lose faith as they see responses lag and vague delivery commitments, impacting the government’s respectability from the perspective of their customers.

Transparency is difficult to deliver. Without transparency into the decision making process, progress against a request, or delivery impactors, citizens are left to make assumptions, that when paired with a lack of trust, tend to have a negative impact on relations with their governing bodies. Do you feel like this has impacted citizen relationships with your organization(s), such as relations with local politicians, or the police department?

So why all of the sudden are these pain points more prevalent? Why is citizen engagement stagnant, or in some cases dropping? Why does the gap between timely delivery and citizen expectation seem to be growing, no matter what? Why is providing transparency so much more difficult today?

The answer is easy: impact of technology trends and transformation. Here are some trends to consider:

Mobile

Mobile gives citizens the power to connect to their government anywhere, anytime–and they have come to expect that level of engagement now that mobile is commonplace. This is good for government, as always-on citizens give organizations the ability to collect more data in context, enabling leaders to prioritize with more accuracy and be more aligned with what citizens care about all around.

Social

Anywhere, anytime citizens tend to be anytime, anywhere customers. This means they have come to expect social interfaces as the user interface as much as they expect mobile accessibility, giving them an always-on receptacle for comments, inquiries, and request status. Social Platforms help governments meet these demands in a scalable, cost conscious way by supplying a transparent and collaborative platform for engagement that is friendly to Q&A at the pace of conversation.

Apps

With technology expanding an organization’s potential reach, apps are becoming more and more popular as an internal asset. They are easily adapted to the next big mobile or tech trend (think apps for the Apple watch), helping organizations modernize/rationalize dated infrastructure at the pace of their citizens.

Connected Products

More and more devices are coming online, revealing data that could never before be captured. While many organizations we talk to see this as a daunting, overwhelming force to be reckoned with, it’s not! By connecting ordinary objects, such as busses, trains, or stoplights to the internet, (made easier to service with apps on a common platform!) citizens will start to expose behavioral patterns that…

Data

Unlock all kinds of data never before detectable. With increased data availability, variety, and context around everyday activities and citizen behavior patterns, officials can better inform government strategy and resource planning. If you are interested in learning more about how to apply and benefit from a data strategy, join us for Philly Innovates. Mayor Michael Nutter and his team are hosting the first-ever Innovation Summit live in the city, and will share how they addressed these tech trends to realize bottom-line benefits.

1:1 Journeys

Customer experience–and therefore citizen experience–is the new differentiator, as new technologies enable customized, personal, more meaningful experiences with a given organization. Just look at how taxi services have morphed so quickly with companies like Lyft and Uber breaking down barriers between private and public sectors, changing the competitive landscape like government has never before seen. There is no reason why agencies can’t take this same approach to citizen services.

Click here to read the entire blog post: http://blogs.salesforce.com/company/2015/01/6-trends-shaping-governmentcitizen-relationships-.html

Process Trumps Innovation in Business Analytics by Tony Consentino

I wanted to reblog this post by Tony Consentino, Ventana Research VP and Research Director,  because it was very insightful and thought provoking. In summary, when using or talking about big data, one should think of terms “What, So what, Now what & Then what”.

Read originally post by clicking this link: Process Trumps Innovation in Business Analytics

The idea of not focusing on innovation is heretical in today’s business culture and media. Yet a recent article in The New Yorker suggests that today’s society and organizations focus too much on innovation and technology. The same may be true for technology in business organizations. Our research provides evidence for my claim.

My analysis on our benchmark research into information optimization shows that organizations perform better in technology and information than in the people and process dimensions. vr_Info_Optim_Maturity_06_oraganization_maturity_by_dimensionsThey face a flood of information that continues to increase in volume and frequency and must use technology to manage and analyze it in the hope of improving their decision-making and competitiveness. It is understandable that many see this as foremost an IT issue. But proficiency in use of technology and even statistical knowledge are not the only capabilities needed to optimize an organization’s use of information and analytics. They also need a framework that complements the usual analytical modeling to ensure that analytics are used correctly and deliver the desired results. Without a process for getting to the right question, users can go off in the wrong direction, producing results that cannot solve the problem.

In terms of business analytics strategy, getting to the right question is a matter of defining goals and terms; when this is done properly, the “noise” of differing meanings is reduced and people can work together efficiently. As we all know, many vr_Big_Data_Analytics_05_terminology_for_big_data_analyticsterms, especially new ones, mean different things to different people, and this can be an impediment to teamwork and achieving of business goals. Our research into big data analytics shows a significant gap in understanding here: Fewer than half of organizations have internal agreement on what big data analytics is. This lack of agreement is a barrier to building a strong analytic process. The best practice is to take time to discover what people really want to know; describing something in detail ensures that everyone is on the same page. Strategic listening is a critical skill, and done right it enables analysts to identify, craft and focus the questions that the organization needs answered through the analytic process.

To develop an effective process and create an adaptive mindset, organizations should instill a Bayesian sensibility. Bayesian analysis, also called posterior probability analysis, starts with assuming an end probability and works backward to determine prior probabilities. In a practical sense, it’s about updating a hypothesis when given new information; it’s about taking all available information and finding where it converges. This is a flexible approach in which beliefs are updated as new information is presented; it values both data and intuition. This mindset also instills strategic listening into the team and into the organization.

For business analytics, the more you know about the category you’re dealing with, the easier it is to separate what is valuable information and hypothesis from what is not. Category knowledge allows you to look at the data from a different perspective and add complex existing knowledge. This in and of itself is a Bayesian approach, and it allows the analyst to iteratively take the investigation in the right direction. This is not to say that intuition should be the analytic starting point. Data is the starting point, but a hypothesis is needed to make sense of the data. Physicist Enrico Fermi pointed out that measurement is the reduction of uncertainty. Analysts should start with a hypothesis and try to disprove it rather than to prove it. From there, iteration is needed to come as close to the truth as possible. Starting with a gut feel and trying to prove it is the wrong approach. The results are rarely surprising and the analysis is likely to add nothing new. Let the data guide the analysis rather than allowing predetermined beliefs to guide the analysis. Technological innovations in exploratory analytics and machine learning support this idea and encourage a data-driven approach.

Bayesian analysis has had a great impact not only on statistics and market insights in recent years, but it has impacted how we view important historical events as well. It is consistent with modern thinking in the fields of technology and machine learning, as well as behavioral economics. For those interested in how the Bayesian philosophy is taking hold in many different disciplines, I recommend a book entitled The Theory That Would Not Die by Sharon Bertsch McGrayne.

A good analytic process, however, needs more than a sensibility for how to derive and think about questions; it needs a tangible method to address the questions and derive business value from the answers. The method I propose can be framed in four steps: what, so what, now what and then what. Moving beyond the “what” (i.e., measurement and data) to the “so what” (i.e., insights) should be a goal of any analysis, yet many organizations are still turning out analysis that does nothing more than state the facts. Maybe 54 percent of people in a study prefer white houses, but why does anyone care? Analysis must move beyond mere findings to answer critical business questions and provide informed insights, implications and ideally full recommendations. That said, if organizations cannot get the instrumentation and the data right, findings and recommendations are subject to scrutiny.

The analytics professional should make sure that the findings, implications and recommendations of the analysis are heard by strategic and operational decision-makers. This is the “now what” step and includes business planning and implementation decisions that are driven by the analytic insights. If those insights do not lead to decision-making or action, the analytic effort has no value. There are a number of things that the analyst can do to make the information heard. A compelling story line that incorporates storytelling techniques, animation and dynamic presentation is a good start. Depending on the size of the initiative, professional videography, implementation of learning systems and change management tools also may be used.

The “then what” represents a closed-loop process in which insights and new data are fed back into the organization’s operational systems. This can be from the perspective of institutional knowledge and learning in the usual human sense which is an imperative in organizations. Our benchmark research into big data and business analytics shows a need for this: Skills and training are substantial obstacles to using big data (for 79%) and analytics (77%) in organizations. This process is similar to machine learning. That is, as new information is brought into the organization, the organization as a whole learns and adapts to current business conditions. This is the goal of the closed-loop analytic process.

Our business technology innovation research finds analytics in the top three priorities in three out of four (74%) organizations; collaboration is a top-three priority in 59 percent. vr_bti_br_technology_innovation_prioritiesBoth analytics and collaboration have a process orientation that uses technology as an enabler of the process. The sooner organizations implement a process framework, the sooner they can achieve success in their analytic efforts. To implement a successful framework such as the one described above, organizations must realize that innovation is not the top priority; rather they need the ability to use innovation to support an adaptable analytic process. The benefits will be wide-ranging, including better understanding of objectives, more targeted analysis, analytical depth and analytical initiatives that have a real impact on decision-making.

Regards,

Tony Cosentino

VP and Research Director