Intelligent Metrix

Data to Metrics to Insight to Intelligent Decisions

Analyst Skills are Hot

analytics and business intelligence jobs

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?

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B2B Social Media – Has Marketing Effectiveness and Efficiency Improved?

How much effort do you need to put into social media before it pays off in B2B? The answer probably has to do with what you expect from social media in the first place. The problem I see for B2B social media marketing is that instead of 1) increasing marketing effectiveness by facilitating sales and deepening customer relationships 2) making marketing more efficient by streamlining process and resources, it may be doing just the opposite.

Marketing Effectiveness

In it’s ability to facilitate sales and deepen the customer relationship, time and again, marketers and sales are unable to translate awareness and conversation trends in social media to sales. In addition, I wonder if connection trends, comment ratios, and sharing ratios are really anything but another way to track existing customer relationships. I’ve narrowed down marketing effectiveness metrics to four (4) key themes. In each case, I’m looking for improvements due to social media.

  • Improve win/loss ratio – Sales may ultimately be responsible for this metric, but marketing is responsible for lead nurturing which contributes to it. The reality is that the awareness marketing that is happening in social media may not be doing anything but providing another outlet for the same content. Tactics such as white paper promotion and communication of offers may appear to increase leads, but views and registrations may ultimately be with the same people already existing within the customer database. In the end, is the social media marketing tactic really changing customer perception during the sales process to make them choose you’re solution more often? I’m not sure it does.
  • Shorten sales cycle – I pose that the sales cycle may actually be lengthening in social media marketing rather than shrinking. Social media appears to be focused more on awareness building than lead generation. This effort is at the beginning stages of the marketing funnel. In fact, because of the conversational nature of social media, it takes longer to convert a ‘getting to know you’ dialogue to a ‘let’s do business’ dialogue. So, instead of coordinating marketing efforts with sales engagement and the decision process, social media is acting more as a fishing net.
  • Increase sales – Due to an increased sales cycle, you may be losing time to help close a deal. Solely focusing on lead nurturing vs. lead conversion can have the affect of creating a state of purgatory for potential customers. Social media, in theory, should help expand your footprint within your customer base by improving customer relationships. However, all social media marketing is doing today is proving a facelift to existing customer forums, white-paper libraries, and transitioning web content to blog content.
  • Reduce churn – There is much buzz around Twitter’s ability to manage customer expectations and improve customer support. Thus, this translates to reducing customer defection. The issue here is that this isn’t happening in the marketing organization. This is a function of customer service. Where marketing fails is that customers are focused on their business, not yours. Conversations in social media marketing today are still more focused on ‘look at me Mr. Customer’. All the customer wants is for you to look at them. It is an effort for customers to utilize and participate in social networks and gather information in social media. There are still too many places the customer has to go to interact. We make it difficult to solidify relationships by managing multiple properties and outlets to connect.

Marketing Efficiency

There is a real hidden cost to utilizing social media for B2B marketing. It is the cost to do business. Due to the number of ways you can connect to customers, it requires a significant amount of effort to cover and manage all the properties. While you can write a single blog and push it out across multiple communities, the lack of diversity in conversations may hurt more than help. Each community probably has a different DNA. One message is not going to be relevant for all. Thus, you have to produce more content across more topics to be effective.

Another aspect of inefficiency is the art of the conversation. For social media to work, it requires a de-centralized communication web to interact with customers. Sales already has this in place as it is what they do every day. Marketing is smaller and has less resources. This puts pressure on the organization to have personalized attention to carry on a conversation. Marketing needs the ability to respond to comments, participate in groups in a conversational manner, and organize discussions and groups around a multitude of topics that customers are interested in. If you go to forums today, there are few that have real conversations happening. Mostly you see blogging and promotional content being posted. This is because it takes a huge amount of bandwidth to truly be interactive with your customers.

Lastly, there is inefficiency to how marketing manages relationships across multiple social media platforms. Again, the number of venues creates chaos in the ability to recognize a single customer. Efforts are duplicative and can create problems in a cohesive conversation and message. Marketing technology needs to be streamlined to better manage relationships.

What’s Next?

As social media marketing has been the buzz and huge shifts are being made to transition and leverage its potential, B2B marketing organizations need to be mindful of what their business charter is and how they meet their goals through effectiveness and efficiency. Social media is just part of the mix, and as with any marketing effort, you don’t want to put all your efforts into one tactic. If not properly monitored against key business benchmarks it can quickly de-focus your marketing efforts and lead to poor performance.

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Social Media: Back to Spreadsheets

It’s a dirty word right now – spreadsheets.  IT departments want to remove our dependence on spreadsheets and convert us over to a secure, controlled, shared, and robust analytic environment.  I would love that!  But, I have a problem, social media.

I’m managing more properties and content that is outside the realm of my corporate environment but I still have to report back and show how it is doing.  The only way I can do this is by using several analytic tools across multiple properties.  I grab the stats I need and punch that into a spreadsheet.  Then, I go to my web analytics reports, grab those stats, and consolidate them with my social media data on my spreadsheet. After that, I consolidate my lead metrics with my internet metrics for a 360° view of my marketing efforts.

It is all very time consuming and open to data entry error.

Business Intelligence is great to track internal process, but it is doing nothing to help track activities outside the corporate environment.  So, I’m stuck with spreadsheets.  Can you help?

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Business Intelligence: Decisions, Decisions

Business Intelligence is all about supporting business decision.”

How many times have you heard that?  It’s become the standard mantra.  It is so ubiquitous that I don’t think anyone questions anymore the validity of the statement.  It just is.  However, this is probably the hardest part to facilitate when building out you business intelligence practice.  Facilitating decisions is what makes BI stragetic.

Just what is the business decision? What does a business decision look like?

Elements of a Business Decision:

  • Purpose:  drive a business outcome – ex: revenue, shareholder value, profitability, market share
  • Position:  leads a company, division, department
  • Point in Time:  transition along a process or environment

A typical approach during the business analysis phase for BI is to at business decisions across a business process and where questions are asked to change behavior in that process.  Although, the difficulty with this level of granularity is that it is too deep.  These transition points are tactical.  Intelligence across this process and at these decision points is important, but you don’t get the strategic value of BI at this level.  You need to look at the outcome of the process and provide a platform that supports the decision of what to do next.  This is the unstated question.

Let’s take an example.  Sales management will always want a perspective on the pipeline and forecast.  This shows them how they are meeting their numbers quarter to quarter.  However, outside of conversion and volume, there are business decisions that sales managers need to make.  Should they adjust their territories to capture new opportunity or shore up existing business?  Are there changes needed in commissions to incent sales people along certain products and services to improve profitability or revenue?   BI can lead sales management with insights that will guide them to optimize their processes and management rather than just data.

Purpose:  market share, revenue, profit
Position:  sales
Point in Time:  aligned to quarterly pipeline and forecast

To align BI to the business decision it is important to include executives in the discussion.  Get beyond the reports they want to see and ask the question about how they manage their business.  Walk through scenarios of what they ask as changes in the market or the business arise and how information can help them make a decision.  The better able you are to see how they manage their business, the more valuable the BI practice will be to supporting the business.

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Stuck in First Gear

porscheBig investments were made in recent years in IT.  IBM, Oracle/Siebel and SAP lead the market and were successful not only with the multi-national enterprise companies but, also with mid-sized companies.  There are a lot of companies out there that have purchased application and data management/data warehouse solutions only to find themselves using a portion of what it could do.  It’s like driving a Porcshe in first gear.

There are some fundamental reasons for this, outside of the fact that companies may feel it is the fault of their sales execute selling them the wrong bill of goods.  IT will blame the business for not knowing what it wants.  The business will blame IT for not getting it.  Doesn’t really matter, there is plenty of blame to go around.  What matters is that now you have a solution that isn’t giving you the benefits that it really could and should be.

Maybe I’m a bit biased since I’m the data chick.  Well, more than a bit.  Regardless, I think that from a data management perspective, companies are failing.  The maniacal focus on process efficiency has drowned out the fact that process runs on data and feeds data.  This focus has put data in the back seat too long and now when we need it to better understand our customers, our business, and make decisions, it is sorely lacking.  Our data lacks unity, structure, definition, and most of all purpose.  Companies simply cannot leverage their information except at very basic levels.  When things are good, this may be okay.  When things are bad, this is a real problem.

What makes this even more sad, is that companies are looking to spend more money on applications and data infrastructure to ‘fix’ the problem.  The promise of the new model and more sophisticated bells and whistles that will solve anything you throw at it is just marketing.  Until you can understand and control what you already have under your hood, getting something bigger, better, and shinier isn’t going to help anymore than it does now.  So, there was no ROI on existing purchases and there won’t be any ROI on new purchases.

There are two things companies need to do to make the investments in enterprise solutions worthwhile:

  • Clean-up the back-end data management practice so that it is fluid with business process and application usage.
  • Have a clear data management strategy for new applications that is fluid and scalable outside of application databases.

Your company may already be embarking on SOA or MDM projects.  But, have you looked at how these new practices will support applications outside of changing the oil?  Can the data drive process?

Today, applications are bogged down because data is treated as something to put in the trunk and horde.  Until data is thought of as fuel, you’re IT investments will stay in 1st gear and never get to 6th.  Now how fun is that?

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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?

business intelligence confusionYou 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.


  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.

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Who I Want at the Business Intelligence Table

Go and look at any guide on implementing Business Intelligence (BI) and invariably executive leadership is touted as a must.  I couldn’t agree more.  In the end, the product of BI is to help them manage the business and make the company successful.  But, the reality is that they look to their department managers and IT teams to work out the details.  Show them the investment and ROI, then get busy on delivering it.

So, what next?  Who do I want on my BI team?

Rather than looking at this in terms of titles and functions, let’s look at this in terms of areas of expertise and levels of project responsibility.  They reason I do this is because as much as process is the typical focus for the typical IT project, BI is a big picture endeavor.  Process will show where data originated from and how data is defined, but it won’t always be a direct linkage to the business objective.  Example:  Predictive analysis might focus on anticipating customer defection.  The process is a component of the customer experience, but the analysis crosses multiple processes.

Business Side:

  • BI Leader:  Strategic thinkers with deep expertise across department practices.  This is where you get bench strength for the project.  You need these strong generalists that see the big picture of customer relationship, financial management, or operational functions as they pertain to business objectives.  These people have been there and done it in some shape or form.  They may have even moved across departments and shifted across areas of expertise.  They know the type of information necessary to be strategic, improve process with information, and how to focus and prioritize information needs.  Where to look: Manager and director positions close to the executive sponsor that have proposed or driven change.
  • BI User:  Analytic champions that have mastered company information providing a range of analysis.  BI Users will be the real developers in the details of the requirements.  They know the company data better than the people that designed the warehouse to manage it.  They can tell you the limitations they have in providing analysis that is meaningful.  Champions have a wide array of analytic techniques from the highly simple to the more complex.  In fact, they could fulfill analytic requests regardless of the department.  They are the scientists in the company.  Where to look:  They support the successful managers, directors, and executives that use data to influence business decisions and priorities.
  • BI Business Analyst:  Business technologist that has experience across multiple types of implementations.   Technologists have a pretty good understanding of how to optimize and fulfill business needs with technology.  Many times they are considered the liaisons between the business and IT.  However, this is more than the note taking of requirements and passing along to IT, project managing, and then ensuring priorities are met.  The technologists are versed in their businesses.  They have migrated from a business role to technology focused role rather than starting from IT and moving to the business.  In addition, they have a depth of technical knowledge and know how to converse and validate recommendations and solutions from IT.  Where to look:  They have most likely been through a couple of solution implementations or data integrations and have a key role in establishing requirements as a business lead or as the lead project manager and business analyst.

IT Side:

  • BI Leader:  Strategic thinkers with deep expertise in driving business outcomes through solutions.  This is the person that talks about the business and rarely about the technology.  They focus on  the strategic implementation and adoption of technology for competitive advantage.  While experts in solutions and infrastructure, the real focus is on efficiency and effectiveness of the business.   They ask, “What problem is the business facing and how do I help?”    They are attuned to company success.  For BI, they need to have a perspective across enterprise applications and data warehouse management.  Where to look:  These are IT leaders that are close to business executives and are goaled on supporting business outcomes.
  • BI Solution Provider:  Solution champions that perfectly unite applications with their back-end information.  They recognize how data relates to the business process as well as the next step of how people use data in the process and to manage the business.  Solution Providers are strategic in their approach to solutions and differentiate between requirement fulfillment and business enablement.  They do what their title says, they come up with solutions rather than just implement technology.  When building applications, data modeling is not far from their thoughts and data warehouse teams are tightly involved in strategy and design.  This is the person that is in the nuts an bolts of best practices of solutions.  Where to look:  These are the people that you turn to for application and data integrations due to M&A activity or legacy system integration and migration.  They spend as much time with the business as they do with IT.
  • BI Implementers:  IT technologies with deep expertise and range of experience in their tools.  BI Implementers will be many spanning across application development and data warehouse.  While not typically in contact with the business during business analysis and design, they are critical to proper development.  They will have silos of expertise in user interfaces, application infrastructure, data warehousing, data management, systems management, data quality, ETL, and database architecture and modeling.  Depending on the size of the company, these silos of expertise will be supported by one or more people.  They will either perform the technical development themselves, or have a team that is experienced to do so.  Where to look: IT Solution Providers that recognize deep strengths in their teams for a strong implementation bench. 

The Often Forgotten One:

Database modeling is one of those aspects of application development and data warehousing that is often left out.  Modeling is a critical factor of success in BI because of its ability to make analysis very easy or force unnecessary issues in performance and programming work-arounds, particularly within ETL and the user-interface.  I can’t stress enough the value of having and expert modeler on hand.  So, if you don’t have a modeler on staff, consider how to fulfill this vital role at the beginning of your design phase.

Using these profiles as a guide to build your team will set you up to successfully design and implement your BI practice.  In addition, you have the ability to see the how the Business and IT balance each other out in experiences and expertise to allow for a good working relationship.  These profiles should also give you a perspective of what, if any consultant or contractor help you need.  The key is to recognize that building your BI team is not unlike hiring an employee and that the more breadth of expertise and experience that person has, the better off you are in the long run.

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Cool Data Visualization – What is That?

Want to help your organization optimize operations, extract market opportunity, see what customers think?  Provide a visual representation in a single slide that tells your senior executives what is happening and what to do.  That is, if they can understand it in a milli-second.

There are a lot of really great algorithms that are creating interesting visual presentations of behavior, influence, and connections across people and topics.  The problem is you might as well be looking at fractals for all the business insight you gain.  It may provide perspective for the resident math geek, but for the average business executive it is just modern art that needs further interpretation.

I remember in college when I first started programming mathematical equations to model data and played with fractals.  It was exciting, creative, and helped me to link data with a tangible result versus a simplified equation or answer.  I used to put fractals up on my website like works of art.  I even included a link to input random numbers for others to create their own.  It was so cool!  Was it practical?

Don’t get me wrong, I love data visualization obviously.  It can simplify very complex analysis to gain insight faster.  What I’m struggling with is needing the ability to connect data visualization with executive intuitiveness.  Heat maps, network graphs, and the variety of data maps I see being generated today are a far cry from what I would bring into a budget meeting let alone show to board members.  More time is spent explaining what executives are looking at than having conversations about business objectives and investments.  It is also not just executives.  Business managers and directors need to understand the business as well.  Pretty is nice, but value is better.

The other aspect that of today’s data visualization leaps is that it disassociates the business from the information.  If only a small group of geeky mathematicians and programmers understand the data, it creates a mysticism that can lead to distrust of information.  If people don’t understand it, they don’t learn, and they don’t improve.

What I hope we can do as really smart statisticians, data analysts, and programmers is make the connection between information and visualization so that it further democratizes insight and empowers our business rather than mystify.

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