Analyst Skills are Hot

BusinessWeek recently reported (listen to pod cast) that there are over 3 million jobs available in the US.  Of that, one of the hottest areas is for analysts. Looking at job posting trends from Indeed, even as the economy has stalled and affected recruitment, analytic and business intelligence jobs are still showing consistent demand.  In fact, even as IBM announced cuts, it has opened up job reqs for analysts to help customers identify opportunities and understand their businesses.  Don’t have all the skills, no problem, if you are an overall good fit IBM will train you.

Which brings up an interesting perspective of the analyst community.  While there are certainly the math and stat majors along with masters and PhD candidates, many of today’s analysts in corporations are self taught and accidentally landed into a data crunching career.  There aren’t many that went to college and said, “Gee, I’d like to be a statistician.”  But, somehow, many analysts have found an affinity toward analyzing data and putting it into context for gaining insight and making business decisions.

Not surprisingly, if you look at barriers in organizations, particularly marketing, and their ability to leverage data to achieve business goals, many feel they don’t have the knowledge to do so.  In fact, they may not know what they need to know to get the right person.  So, these coveted positions continue to remain unfilled, waiting for the right candidates to show up .  How long should your business wait to find the right person and what is that costing you in missed opportunity?

Finding the Right Candidates

When hiring, I’ve typically focused an one’s aptitude and capability to analyze information rather than the tools used or complexity of analysis they have done.  The first reason is that there are very few out there that would fit the bill and if they do it takes a lot of money to bring them in.  The second is that while I want analysts to understand standards and procedures to analyze data, I don’t want individuals with rigid and unimaginative thinking that can constrict their ability to look at information in a new way for better insight.    When it comes to complexity, investing in the proper training/education, and mentoring them through projects works the best.  This way their learning is specific to the business need rather than a broad based approach to statistics and analysis.  Essentially, provide the academic guidance within a relevant corporate environment and application.  Overall, candidates should be inquisitive, creative, and obsessed with data, and self starting.

I know others that have strong relationships with universities and pluck candidates out of programs that have provided applicable experiences in analysis.  This is a favorite of research organizations where they partner with professors on a regular basis.  In addition, there are associations and institutes that offer advanced research courses that up and coming analysts attend and are resources to help find those with a high aptitude for analysis.  Many times professors, leading statisticians, and research professionals teach these courses and can be conduits to finding the right candidates.

How do You Fill Your Analyst Positions?

If you regularly hire analysts, what are you looking for?  What have you found makes an analyst successful in your company?  And, what advice do you have to help those that are having trouble filling analyst positions?

Filed under: Hiring, analyst skills, analysts, Analytics, business intelligence, hiring analysts, Knowledge Management, statistical analysis

Why Business Intelligence is So Difficult

Reading the buzz on the Jim Davis’s presentation at SAS Global Executive Forum, what it made me realize is that if as an industry we can’t agree on what Business Intelligence is or Business Analytics, how are we supposed to make sense of it in implementation?

You have analytics players, enterprise application vendors, business process consultants, and analysts all trying to sell the ‘hype’ of a better way to analyze your business and makes decisions.    SAS wants to sell their analytic solution that really pioneered data mining in businesses.  Oracle and IBM wants to push dashboard solutions that links to business processes and their enterprise applications.  Gartner that tries to tie together people, process, and technology but is really is focused on what technology to buy.  Then, you have consultants that are trying to help you implement the technology even as they document your processes.  The problem is that it’s all boiling down to the one with the best tool wins.

Enter in the ‘Business’ and now you have a problem.  All they want to know is how they can meet their business objectives.  IT is trying to sell the solution and make them understand the technology, and the business glazes over and can’t figure out what to focus on.  I’ve sat in these discussions where IT tells me, “You tell us what to do, we’ll do it.  Don’t worry about the solution.”  It is open ended.  This leads to IT unable to work towards tangible goals and results.  The business walks away frustrated, projects run from months into years, and original budgets are thrown out the window.  I liken these projects to Boston’s Big Dig.

Neil Raden provided a perfect way to get through the fluff and hype that surrounds analytics and business intelligence. See article From BI to Business Analytics, It’s All Fluff

“I don’t like the term business analytics; it doesn’t tell me anything. Frankly, I think business intelligence as a term is downright laughable, too. What does that mean? Is integrating data intelligence? Is generating reports intelligence? Maybe its informing, but isn’t intelligence something you HAVE not something you do? Does doing what we call BI lead to intelligence, or just some information? A long time ago we called this decision support, and that gets my vote.”

So here’s my take on what steps to take when and how to venture into BI and analytic solutions.

Steps:

1. What decisions need to be made?
2. At what point in our business and business processes are these decisions made?
3. What information is needed at these points?
4. How should our applications and data provide this information – triggers or visualization?

See the steps?  It starts with the business decion and ends in the technology.  So, when you begin to review vendors and solutions, make sure you have steps 1,2,3 in mind before you determine how to solve step 4.

Filed under: business intelligence, Decision Cycle, performance management, Analytics, business analytics, business intelligence, Business process, Data mining, decision support, performance management