5 Tips For Building a Project Team

The secret to high ROI is in the PEOPLE!  So today, I am going to focus on 5 tips for building a project team and attracting the superstars in your organization to beg to be on your project.  Many companies just assign whoever has some availability; and, often times, this is a recent hire with no experience in the company.  It’s time to STOP this behavior NOW!  Don’t you want the best talent on your business analytics project? But how?

Picture a world where the top talent in the organization is fighting to be on your Business Analytics Project.  Finance, Marketing, Sales, IT… all the superstars come out begging to be moved onto the Business Analytics team.  Seems a little farfetched?  I don’t believe so.

I believe superstar talent has some common denominators.  They strive to change the world, they believe in doing things the right way, they don’t believe in the word “no”, and they rise to the challenge to solve complex problems.  They love to be around people like themselves.  They are creative, bright and tend to bend the rules a little to get results.

Now that we have an attribute profile, what are some ways of building a project team and creating an environment that will get these people begging to move to Business Analytics projects?

  1. You MUST create an environment where they can thrive, grow and shine!  Create an opportunity where you are satisfying their needs; play to their passions and you will have them jumping out of bed totally jazzed to get to work.
  2. Define and Communicate the Importance and Purpose of your Project.  Have the highest level executive possible announce how Business Analytics will help the organization grow and change the lives of customers and employees.  (Ideally, this will be related to the purpose, or why your organization exists).  Coach them to make this sound like the most important project in the organization, because it is!
  3. Executive Support – This requires top executives and managers to communicate to their teams that if someone wishes to transfer to the Business Analytics department, it is acceptable.  Managers cannot hoard their talent.  They must understand the importance of Business Analytics to the growth and profitability of the organization.
  4. Plan and create a project culture that inspires creativity and cooperation.  This needs to be done in the very first team meeting.  The organizer/manager must bring energy and passion, and must establish project team rules.
  5. Celebrate the wins as a team.  The project will take many twists and turns along the way.  Celebrate the small wins and make it public, giving praise to all who supported the efforts, even non-team members.  And don’t forget to laugh, a lot.

Build the Team, Build a Culture and Make IT Happen! It will put the FUN back in your career. Contact us at Sales@LodestarSolutions.com for more information!

5 Tips to Succeed at Cognos Analytics

With Analytics becoming more mainstream, we still see many companies shying away from it; perhaps because they have been burned by previous attempts. Here are five tips for any organization looking to turn the corner and start to Succeed at Cognos Analytics.

  1. Make data and analysis available to employees: Analytics veterans will tell you there is big value in allowing employees to see and use data. The power transfer that occurs when this is permitted inspires insights in employees’ own work, which helps analytics programs grow and evolve; thereby providing even more value and improvement. Be sure to always ask for users’ assistance and to put some of their ideas to work. These insights will help guide the progression of the project, all while strengthening employees’ commitment to the data analytics strategy.
  2. Return on Investment should be measured early & often: Recording wins from data analytics projects is important; however, it is a bottom line requirement and may not be enough to continue to win budgetary support. Times are tight for organizations of all sizes and in all markets, so when it comes time to verify that dollars were well spent on your data analytics efforts, be sure to include: clear measurements on cost benefit (in dollars), hours of employee time saved (in hours and dollars – and include value of re-assignments), as well as the improved outcomes that were seen (that may not have a direct monetary value i.e. improved employee morale, improved customer satisfaction, etc.).
  3. Hire an expert: Some organizations opt to skip consulting assistance in lieu of pre-recorded training modules and learn to do it themselves for the sake of saving a few bucks. Unfortunately, this mindset causes sluggish returns on the Analytics investment, and we have seen analytics programs get cut for this very reason. Go ahead and get yourself that consultant and ask for a start-up package with training, or better yet, if you can find an expert – HIRE THEM, and then learn from them! Their wisdom and experience can speed your first few projects into quick wins that will help boost data-use culture within your department and maybe across the organization. These wins will also help you continue to get budget allocations, and when word gets around about your success, you may be surprised to see who else from your company comes knocking at your door.
  4. Get to the point: Top executives’ support is vital to keep analytics projects afloat, and the information and insights analysts develop are vital to top executives’ decision making. “Clear, concise and, most of all, brief” should be your mantra if you are presenting at the executive level. Speak as if you are an executive and be sure you are presenting the product of your analysis, and not the analysis itself. In order to get top leaders to support your data analytics program, they must understand the results of your analysis and how they align to achieving the organization’s overall mission(s). This is actually the largest piece we find lacking in the talent pool for analysts – people with statistical and/or data mining experience AND Business Sense.
  5. Seek to envelop the organization in data-use culture: Eventually, analytics will be standard operating procedure in all areas of your organization. However, this will take time and numerous successful analytics projects to win over management at all levels. When this happens, there will be a need for on-the-job analytics training for employees to meet the new demand from management (again – hire an expert!). The return on investment for analytics projects (particularly predictive analytics) is so high that the cost for training and/or hiring an expert ends up paying for itself through speedier results and measurable ROI.

These are just a few highlights from data analytics veterans who have seen just about everything. If you have been reluctant to get started, or feel as if you have been burned before but are still feeling interested – we are happy to help! Contact us at Sales@LodestarSolutions.com.

4 Reasons Analytics Software Deployments Fail

With all of the talk about Big Data and Advanced Analytics, many companies are under the false impression that if they purchase a software package or invest in hardware, that will be all they need to be successful.  In fact, many companies are finding that they are not seeing the return on investment they had expected.  The problem is that deploying an analytic tool is easy.  Understanding how the data might be used is less clear.  There are a couple things to consider on why your Analytics Software Deployments Fail:

1. Not Aligning the Correct Resources

Who is deploying your Advanced Analytic applications?  Is it IT, or the business?  The correct answer should be both. Lodestar Solutions encourages a team consisting of IT people who understand the data and the business as well as business people who are comfortable thinking outside of the box.  Typically, you want a motivated business person who is analytical.  I don’t believe you can teach people to be analytical.  As your organization moves to rely more on analytics, this is a skill set you might want to assess more in your hiring.

2. Not Knowing all the Software has to Offer

All software has its limits, and typically, a hundred ways to accomplish the same thing.  Working with a partner who knows all the options the software provides will help you focus on the end result.  The biggest risk factor is usually the quality of the data.  To get rapid results, you may need to plan for temporary solutions. Your job is to provide the experience of your business.  Your implementation partner may have to be MacGuyver and leverage areas of the software you never knew existed. Sure there are best practices, but I doubt you have unlimited time, money and resources. Be realistic about the risks, and you will set proper expectation for success.

3. Organizations don’t Encourage Stepping out of the Box

It’s time to step out of the comfort zone and try new things.  Asking questions of the data that may have never been asked before can result in interesting findings.  Many organizations don’t encourage people to push the boundaries.  Creating a culture in which being inquisitive and learning is encouraged will help the organization increase the benefits of Analytics.

4. Focus on Solving Deployment and Not the Business Problem

Many IT projects are so focused on budget and timelines they lose focus on the real goal.  Business Analytics is about relating the behavior of people and businesses to what you have to offer the clients.  Behaviors are dynamic, and therefore, sometimes during implementations we discover there’s a more effective way that was not foreseeable.  This can result in delays in projects, but a constant examination of the ROI of solving the business problem as opposed to focusing on the original timeline and budget, can lead to better than expected results.

Lodestar Solutions encourages you to work with a partner who understands the technology and has the ability to work well with your business group to interpret the results.  Call us for more information 813-254-2040.

Here’s an interesting article we recommend you read from Harvard Business Review on why Analytics software deployments fail: