PI Practice

Performance Improvement

How do you deliver year-on-year growth?

help you deliver measurable and sustainable improvement in the performance of your business by focusing on the areas of Finance, Customer, and Supply Chain.

Finance

• Transforming your finance operating model
• Designing and managing outsourcing, offshoring and shared service center arrangements
• Sharpening your performance management framework
• Designing and implementing financial systems
• Conceiving and implementing enterprise cost management systems

Customer

• Develop and deploy your market and customer strategy
• Develop and help implement insightful customer analytics that allow you to understand and anticipate customer needs
• Develop pricing, promotion, channel and product strategies that improve your margin and increase your profits
• Improve customer service management
• Improve marketing and sales performance
• Streamline and accelerate your collections processes

Supply Chain

• Provide insight into the health of supply chains by using a robust set of data analytics
• Transform global supply chains through a cross-disciplinary approach spanning operations, tax and risk
• Review, improve and assess risk of procurement functions to realize long-term, sustainable benefits
• Improve supply chains and infrastructure in emerging markets as a powerful catalyst to secure new market share and drive revenue growth
• Integrate environmental, sustainable and low carbon aspects into end-to-end supply chains

Underpinning our performance improvement capabilities are our strengths and skills in day-to-day operations, management and strategic decision-making. These skills are concentrated in the four supporting areas of:

• People and organizational change
• IT advisory
• Strategic direction
• Program management

Mentor vs. Advisor

it's a good opportunity for them to practice saying 'no' . We can brief her on the talk track --e.g. i) adjusting and not abandoning the relationship, ii) shifting to an advisory relationship (focusing on discrete issues) from a mentoring relationship (where effective mentors get to know mentees--through frequent updates--psychologically, personally, professionally so to provide relevant, tailored advice).

Leadership Convo

1)      Not addressed well/at all- why motivated, direct role, effect, lessons elarend

2)      Create future leaders, coach and jot deleate – when working with group, how do you deal with weakest link? Keep strongest person motivated?

a.       ME: have conversations – tactics- admit it’s so difficult. Do me a favor and try this with me. Not enjoy doing – diff skill sets

b.       Don’t call them out

3)      Potential impact – incorporate new and external resources

Discussion

-          Dec’11 Haas shootihg incident. Negotiate on priorities agaist RA assessment

-          Adjuticate the alumni scholarship

-          Vapur water bottle- UCB is 40% asian american. Community-based research

-          $1600 fixed cost to raise $2500 –

-          Ron Howard- movie director

-          the blue sweater‘ book

-          Structural changes—buildling a team.

-          Hot topic – 2.7% shrinkage vs. 1.9% shrinkage

-          Cohort leadership. Service leadership. Passion/integriy

Takeaways

-          Add your own introduction. Use more ‚I“. Say the what where when who how

-          Keep asking for feedback—after first round

-          Say questions slowly. Suggest a time frame.

-          Tactics: Jamba juice- keep calling. Finance chair need specific directions on how much to raise

USF Masters in Data Analytics Class

From data to information --Unstructured, scrappy data

statistics and machine learning, 

. “They can take a data set and model it mathematically and understand the math required to build those models; they can actually do that, which means they have the engineering skills…and finally they are someone who can find insights and tell stories from their data. That means asking the right questions, and that is usually the hardest piece.”

  

Computational Analytics I (2)
Data mining, including classification and association. Rules, trees, and classifiers. Clustering. Data cleaning. Use of relational and non-relational (NoSQL) data stores.

Business Analytics I (2)
Application of basic analytical methods to business problems. Topics include market basket analysis, management science, optimization and satisficing techniques, survey design. 

Computational Analytics II (2)
Topics include: advanced data mining, text mining, modeling of problems for hadoop/MapReduce, network analysis, managing large data sets. 

Ragnar Race in Sept '12

And of course, the team is looking for ppl to run Legs #4 and #6 (both have the 'very hard' sections). Only #1, 3, 7, and 12 don't have the very hard but #9 and #10 are hardcore.

http://imgur.com/delete/1dw6tLGz2iNWtRK