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cezarovidiu

10 Reasons Why CEOs Don't Understand Their Customers - Forbes - 0 views

  • 1) Do bad customer experiences cause people to switch brands? In a 2011 research project conducted by CX application vendor RightNow, 89% of consumers said that yes, a bad experience has spurred them to switch brands. But in the brand-new study of business-executive perceptions that’s the subject of this column, only 49% of the surveyed executives said yes.  QUESTION: What steps do you need to take to close this dangerous perception gap? 2) While 97% of executives say CX is critical to the success of their company, and 91% say they’re committed to making their company a CX leader, only 20% would rate their own CX initiatives as “advanced,” with a dedicated CX leader in place, initial projects pushed to the optimization phase, and the overall project extended to new channels and groups . QUESTION: What are the obstacles preventing you from aligning your actions with your words? If you say it’s a “budget” issue, aren’t you really talking about strategic priorities rather than line items? 3) Most companies have a clear and direct understanding of the looming CX challenge and the powerful interaction of social media. The study found that the top two drivers for CX initiatives are (a) rising expectations from customers (59%),  and (b) the impact of social media on customers’ ability to broadcast good and bad experiences (37%). Now, even if you’re able to somehow rationalize those findings, here’s one that not even the most-accommodating executive can dismiss:
  • 4) Being a CX laggard can cost those companies many tens of millions or even hundreds of millions of dollars in lost revenue: executives estimated that the lack of positive, consistent, and brand-relevant customer experience can cause them to lose out on a staggering 20% in annual revenue.
  • Worse yet, all that money’s likely to wind up in the pockets of your competitors!
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  • 5) While 81% of execs said they believe that social media is an essential ingredient in delivering great customer experiences, 35% of responding companies still do not have social media for sales channels, and another 35% still do not have social media for customer service. QUESTION: How do you plan to close that dangerous gap?
cezarovidiu

Top Mistakes to Avoid in Analytics Implementations | StatSlice Business Intelligence an... - 0 views

  • Mistake 1.  Not putting a strong interdisciplinary team together. It is impossible to put together an analytics platform without understanding the needs of the customers who will use it.  Sounds simple, right?  Who wouldn’t do that?  You’d be surprised how many analytics projects are wrapped up by IT because “they think” they know the customer needs.  Not assembling the right team is clearly the biggest mistake companies make.  Many times what is on your mind (and if you’re an IT person willing to admit it) is that you are considering converting all those favorite company reports.  Your goal should not be that.  Your goal is to create a system—human engineered with customers, financial people, IT folks, analysts, and others—that give people new and exciting ways to look at information.  It should give you new insights. New competitive information.  If you don’t get the right team put together, you’ll find someone longing for the good old days and their old dusty reports.  Or worse yet, still finding ways to generate those old dusty reports. Mistake 2.  Not having the right talent to design, build, run and update your analytics system.  It is undeniable that there is now high demand for business analytics specialists.  There are not a lot of them out there that really know what to do unless they’ve been burned a few times and have survived and then built successful BA systems.  This is reflected by the fact you see so many analytics vendors offer, or often recommend, third-party consulting and training to help the organization develop their business analytic skills.  Work hard to build a three-way partnership between the vendor, your own team, and an implementation partner.  If you develop those relationships, risk of failure goes way down.
  • Mistake 3.  Putting the wrong kind of analyst or designer on the project. This is somewhat related to Mistake 2 but with some subtle differences.  People have different skillsets so you need to make sure the person you’re considering to put on the project is the right “kind.”  For example, when you put the design together you need both drill-down and summary models.  Both have different types of users.  Does this person know how to do both?  Or, for example, inexperience in an analyst might lead to them believing vendor claims and not be able to verify them as to functionality or time to implement. Mistake 4.  Not understanding how clean the data is you are getting and the time frame to get it clean.  Profile your data to understand the quality of your source data.  This will allow you to adjust your system accordingly to compensate for some of those issues or more importantly push data fixes to your source systems.  Ensure high quality data or your risk upsetting your customers.  If you don’t have a good understanding of the quality of your data, you could easily find yourself way behind schedule even though the actual analytics and business intelligence framework you are building is coming along fine. Mistake 5.  Picking the wrong tools.  How often do organizations buy software tools that just sit on the shelve?  This often comes from management rushing into a quick decision based on a few demos they have seen.  Picking the right analytics tools requires an in-depth understanding of your requirements as well as the strengths and weaknesses of the tools you are evaluating.  The best way to achieve this understanding is by getting an unbiased implementation partner to build a proof of concept with a subset of your own data and prove out the functionality of the tools you are considering. Bottom Line.  Think things through carefully. Make sure you put the right team together.  Have a data cleansing plan.  If the hype sounds too good to be true—have someone prove it to you.
cezarovidiu

Filling a Critical Role in Business Today: The Data Translator - Microsoft Business Int... - 0 views

  • a lot of articles calling data scientists and statisticians the jobs of the future
  • there are more immediate needs that, when addressed, will have a much greater business impact.
  • Right now we have huge opportunities to make the data more accessible, more “joinable” and more consumable. Leaders don’t want more data – they want more information they can use to run their businesses.
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  • Every company has hundreds of millions of records about their sales, expenses, employees and so on, with dozens of insights yet to be discovered through simple comparison or triangulation of relevant data.
  • Why don’t we focus on this? I think because it’s very difficult to do – being successful in this “data translator” role requires a unique set of skills and knowledge, the combination of which I call the BASE skillset: Business understanding Ability to synthetize and simplify Storytelling skills Expertise in data visualization
  • Business Understanding This one seems obvious, but it doesn’t mean simply understanding the financials of a business. Rather, it means truly knowing the operational details, the incentives, the install base, market growth, penetration, the competition, etc. An analyst can’t just know the technical aspect of a report or the math behind the numbers, but what is truly driving a pattern in terms of product quality, competition, incentives and/or offerings. The best analysts are able to mathematically isolate the key levers of a trend and then suggest actions to react to or take advantage of those trends. Ability to Synthetize and Simplify This is, in my opinion, the most underrated and underappreciated skill. Combing through thousands of data points and netting out 3-4 key issues in under 10 minutes, and then communicating these to a group of execs with very different analytical skills, is truly difficult. The key is to make it simple but not simplistic, which means you still capture the complexity even as you get to the few core insights. It requires a very thorough effort to gather all the relevant information before categorizing, prioritizing and deciding if it is significant. After a while, you become an expert and can sniff things out quickly. At the same time, there is the danger of missing anomalies when you jump to conclusions based only on a summary look.
  • Storytelling Skills There are stages that should be followed when explaining complex ideas, something data translators are frequently expected to do. The best storytellers start by giving context and trying to couple the current discussion to something the audience already knows, ensuring the story is well structured and connected. We have to move from a “buffet style” business review with thousands of numbers packed in tables to a layered approach that will guide the audience to focus first on the most relevant messages, diving deeper only when necessary. Minto Pyramid Principles, which are built around a process for organizing thought and communication, are helpful in making sure you really focus on what is important and relevant, versus being obsessed in telling every fact. Expertise in Data Visualization I am glad to finally see so much focus on Information Visualization and I believe this is correlated to the explosion of data. Traditional methods of organizing data do not facilitate an intuitive understanding of key information points or trends. For instance, the two examples below contain data on car sales across the U.S. The first, an alphabetized list, is much less intuitive than the second, which shows those sales on a map in Power View. With Power View, right away you can identify the states with the highest sales: CA, FL, TX, NY. (Workbook available here)
  • There is no better way to see patterns or trends than data visualization, making expertise in this area – both technical and analytical – critical for data translators.
cezarovidiu

Moving Sugar to Another Server - SugarCRM Support Site - 0 views

    • cezarovidiu
       
      japtone   Senior Member Join Date Nov 2010 Posts 49  Re: Transferring SugarCRM to a new server If you're using Linux try to have the same version of PHP, Apache, and DB (MySQL for instance) in order to avoid compatibility issues. In your production server tar up the sugarcrm root directory, transfer it to the new server and untar wherever your new root directory will be.  Next take a db dump of your database, transfer it to the new server and do a restore. Make sure apache is configured on the new server to point to the root of sugarcrm and start it up.  Make sure to modify config.php to account for any change in paths and hostname.  that's what I've found to be the easiest way to 'clone' sugar.
  • mysqldump -h localhost -u [MySQL user, e.g. root] -p[database password] -c --add-drop-table --add-locks --all --quick --lock-tables [name of the database] > sqldump.sql
  • Extract the Database
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  • Copy Filesystem Copy all your files to the new server.  This can be done simply by locating the root directory on your old instance and copy and pasting it to the new server location.
  • Import Database Import the mysql database into the new server.  Here's how you would restore your custback.sql file to the Customers database. mysql -u sadmin -p pass21 Customers < custback.sql Here's the general format you would follow: mysql -u [username] -p [password] [database_to_restore] < [backupfile]
  • Check Files and Permissions Check Config.php Open <sugarroot/config.php> and make sure that all settings still apply to the new server, such as: array ( 'db_host_name' => 'localhost', 'db_user_name' => 'root', 'db_password' => 'PASSWORD', 'db_name' => 'DATABASE_NAME', 'db_type' => 'mysql', ), 'site_url' =>, etc...
  • Check htaccess Open <sugarroot/.htaccess> and ensure that the new server URLs are used correctly.
  • Check Permissions Check that the permissions are correct on the new server. That is the entire custom and cache directories (and all the sub directories) in addition to the config.php file are owned and writable by the user that runs the application on the server.
cezarovidiu

Rittman Mead Consulting » Blog Archive » Using OBIEE against Transactional Sc... - 0 views

  • The best practice in business intelligence delivery is always to build a data warehouse.
  • Pure transactional reporting is problematic. There are, of course, the usual performance issues. Equally troublesome is the difficulty in distilling a physical model down to a format that is easy for business users to understand. Dimensional models are typically the way business users envision their business: simple, inclusive structures for each entity. The standard OLTP data model that takes two of the four walls in the conference room to display will never make sense to your average business user.
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