To succeed in the Age of the Customer, business and IT leaders that that support “front-office” business processes cannot afford failed technology initiatives. CRM technology projects can be costly, affect many employees within the organization, and can suffer from a lack of vendor support.
To understand the types and prevalence of the pitfalls that you need to navigate, I recently did a survey of CRM practioners. Working in partnership with CustomerThink, Forrester collected opinions from over 500 individuals who had been involved in a CRM technology project as a business professional in Sales, Marketing, Customer Service, or IT within the last 36 months. Respondents evaluated 88 project risk factors, in four categories: strategy (business goals and objectives); process (procedures and business rules); technology (applications and infrastructure); and, people (organizational structure, skills and incentives).
I will report our findings in more detail in up-coming blogs, but here are some initial insights.
To achieve CRM technology deployment success requires a balanced approach. Focus on all four fundamental success factors:
■ Process. Nearly half (44%) agreed their CRM projects faced problems grounded in: poor or insufficient definition of business requirements; inadequate business process designs; and, the need to customize solutions to fit unique organizational requirements.
■ People. More than two-fifths (42%) agreed that their problems were "people" issues: such as slow user adoption; inadequate attention paid to change management and training; and, difficulties in aligning the organizational culture with new ways of working.
Ari Kaplan is a real moneyball guy. As President of Ariball, he has worked with more than half of all the MLB organizations to evaluate players for maximum return on the baseball club's investment. But, Ari is much more than just a moneyball guy, he is also a computer scientist, a data scientist, and has the business acumen to produce dramatic results for the teams he works with. He is the real deal. Forrester TechnoPolitics caught up with Ari at Predictive Analytics World in Chicago to ask him how Big Data and the role of the data scientist will advance the science of moneyball.
Too little data, too much data, inaccessible data, reports and dashboard that take too long to produce and often aren’t fit for purpose, analytics tools that can only be used by a handful of trained specialists – the list of complaints about business intelligence (BI) delivery is long, and IT is often seen as part of the problem. At the same time, BI has been a top implementation priority for organizations for a number of years now, as firms clearly recognize the value of data and analytics when it comes to improving decisions and outcomes.
So what can you do to make sure that your BI initiative doesn't end up on the scrap heap of failed projects? Seeking answers to this question isn't unique to BI projects — but there is an added sense of urgency in the BI context, given that BI-related endeavors are typically difficult to get off the ground, and there are horror stories aplenty of big-ticket BI investments that haven’t yielded the desired benefit.
In a recent research project, we set out to discover what sets apart successful BI projects from those that struggle. The best practices we identified may seem obvious, but they are what differentiates those whose BI projects fail to meet business needs (or fail altogether) from those whose projects are successful. Overall, it’s about finding the right balance between business and IT when it comes to responsibilities and tasks – neither party can go it alone. The six key best practices are:
· Put the business into business intelligence.
· Be agile, and aim to deliver self-service.
· Establish a solid foundation for your data as well your BI initiative.
What a strange summer this has been! From Boston to London to Paris to Turin, the weather has offered weekly and even daily reversals, with continuous change from sun to rain, from hot and damp to cool and crisp. I missed a nice spring season. Even today, from 35º-38º Celsius (95º-100º Fahrenheit), we just went to 22º Celsius (71º Fahrenheit) with a perfect storm! A continuous climate and sudden change is quite unusual in some of these countries. Certainly it is where the Azores Anticyclone usually dominates from mid-late June to mid-late August, offering a stable summer. How many times have you had to change plans because you discover weather is about to change!?
You might be thinking, "What does this have to do with this AD&D blog?" It’s about change! I am wondering if, in our daily lives, getting used to unexpected conditions and having to handle continuous change favors a mindset where change is just something we have to deal with and not fight. A new mindset very much needed given the change we see ahead in how we develop, test, and deploy software!
My focus in this blog is testing, although the first change we need to get used to is that we can’t talk any longer about testing in an isolated fashion! Testing is getting more and more interconnected in a continuous feedback loop with development and deployment. (See my colleague Kurt Bittner's report on continuous delivery; I could not agree more with what Kurt says there!)
Mobile app developers need to work fast. Mobile backend-as-a-service (mBaaS) providers such as Kinvey, StackMob, And AnyPresence can help according to Forrester Senior Analyst Michael Facemire. But, that's not all. Mike says using mBaaS will help you "focus on the things that will get you a better job, make more money, actually have fun at work, and be proud of what you're doing". I don't know about you, but I'm in. Watch this episode of Instant Insight to learn what mBaaS in and why you should use it.(2 minutes)
About Forrester Instant Insight
Navigating the fast-changing world of business technology is a constant challenge. Forrester Instant Insight aims to provide simple, complete answers to some popular questions. Our goal: You will watch the video and be enlightened in 5 minutes or less.
In the days when web applications were king, this type of insight was doable with simple web analytics and similar tools. Today, continual experience optimization is much more difficult because of:
Multiple interaction channels. You must collect, correlate, and analyze data in a coherent way across multiple channels of customer interaction. A single customer interaction may cross between channels or even use more than one channel at the same time.
Many back end servers. You must integrate data from multiple back end servers including recommendation engines, commerce, mobile application servers, digital asset management, community, collaboration, messaging, and more.
The need for rapid change. You must quickly change any or all of your digital experiences and back end services based on what you’ve learned.
The need for contextual experiences. You must use each individual customer’s context to dynamically adjust experiences in real-time.
Market conditions are changing quickly; firms need to make the best possible business decisions at the right time and base them on timely, accurate, and relevant information from business intelligence (BI) solutions. The repercussions of not handling BI change well are especially painful and may include lost revenue, lower staff morale and productivity, continued proliferation of shadow IT BI applications, and unwanted employee departures. Ineffective change management often lies in the process of preparing the people affected by change rather than in planning the technology implementation. Firms that fail to prepare employees for enterprise BI change early enough or well enough will be left behind. They need to implement a multifaceted series of activities ranging from management communication about why change is needed to in-depth, role-appropriate employee training.
Why change management is so critical? Most strategic business events, like mergers, are high-risk initiatives involving major changes over two or more years; others, such as restructuring, must be implemented in six months. In the case of BI, some changes might need to happen within a few weeks or even days. All changes will lead to either achieving or failing to achieve a business result. There are seven major categories of business and organizational change:
Business process changes
New technology implementations
Changes to business process outsourcing or IT sourcing
Initial business intelligence (BI) ployment efforts are often difficult to predict and may dwarf the investment you made in BI platform software. The effort and costs associated with professional services, whether you use internal staff or hire contractors, depend not only on the complexity of business requirements like metrics, measures, reports, dashboards, and alerts, but also on the number of data sources you are integrating, the complexity of your data integration processes, and logical and physical data modeling. At the very least Forrester recommends considering the following components and their complexity to estimate development, system integration and deployment effort:
What’s it like to get Google Glass? It’s fun. It’s unique. Watch this special episode of Forrester TechnoPolitics to get an inside look at the Google Glass “shopping” experience in New York City. This may be a preview of how Google plans to create a high-end shopping experience to outdo Apple stores. You may also be interested in Google I/O 2013 Conference: A Great Time To Be A Developer.