Data-Driven Innovation Management
For Innovation Product Portfolio Executives:
HOW TO BOOST PRODUCT LAUNCH AND PROBABILITY OF SUCCESS BY 2X
GlaxoSmithKline (GSK) increased growth in innovation pipeline value from 2% To 5% while saving 30% of the executive’s time.
Pauline Lim - Director of Global Innovation Portfolio
The Core Concept
You can uplift your revenue and launch products 2x faster with 2x the probability of success if you implement a well-designed data-driven innovation portfolio management process.
However, most innovation portfolio executives are still managing individual projects technically without implementing a holistic data-driven innovation governance model to manage the entire portfolio.
The Founders
Amr Mostafa
Amr Mostafa
Amr Mostafa
Amr is a founder of an NYC-based data science and analytics company that worked with multiple innovation fortune 500 companies.
Ayman Ghoneam
Amr Mostafa
Amr Mostafa
Ayman is a founder of a startup growth agency and also founded
a full-fledged investment portfolio management company.
Who We Worked With
The 5 Steps explained
Step 1: Implement a holistic Product Portfolio Management
Step 2: Utilize Product/Product Portfolio Management Platform
Step 2: Utilize Product/Product Portfolio Management Platform
The Challenge
"According to Gartner research, out of $1 to $2 trillion invested in IT deployments in North America annually 30% or $300 to $600 billion is wasted. A lot of the waste can be attributed to not “doing the right work”. Product and Portfolio Management (PPM) approach highlights which initiatives should be approved based on strategy alignment and not because their sponsors shout the loudest."
- Source: PMI (2006). Product portfolio management techniques.
The Solution
1- Strategic Direction
2- Aligning Process
3- Monitoring & Controlling Process
“Implementing a Product/Product Portfolio Management model results in launching Products 2x faster which ensures strategy is in line with funding opportunities and therefore maximizing funds possibilities for Products and increases profits”
Step 2: Utilize Product/Product Portfolio Management Platform
Step 2: Utilize Product/Product Portfolio Management Platform
Step 2: Utilize Product/Product Portfolio Management Platform
The Challenge
“Only 17 percent say the strategically relevant Products at their companies are very well aligned with strategy overall. Sixty-one percent say they are only somewhat aligned. More striking, only around 10 percent believe their formal processes used to manage strategic Products strongly enhance strategic adaptability, agility, speed, or success in implementation. About half the time, the impact is negligible or even negative.”
- Source: PMI (2015). Implementing the Product Portfolio: A Vital C-Suite Focus.
The Solution
1- Single Source of Truth
2- Total Pipeline Commercial performance.
3- Visibility on portfolio balance and pipeline progression.
“Implementing a Product/Project portfolio management central data repository leads to Alignment among stakeholders and decision-makers which results in 2x resources utilization”
Step 3: Implement A Data-Driven Product Prioritization Model
Step 3: Implement A Data-Driven Product Prioritization Model
Step 3: Implement A Data-Driven Product Prioritization Model
The Challenge
“According to the EIU research, only 28 percent of senior leaders said that their organizations translate KPI data into information on portfolio risk; and only 34 percent translate it into ROI metrics on portfolio profitability and the delivery of objectives”. - Source: PMI (2015). Delivering on Strategy: The Power of Portfolio Management.
The Solution
1- A standardized prioritization model.
2- Compare performance to benchmarks.
3- Visibility on risk factors that require action.
“Data-driven Product/product prioritization results in 2x return on investment”
Step 4: Implement Data-Driven Resource Management Model
Step 3: Implement A Data-Driven Product Prioritization Model
Step 3: Implement A Data-Driven Product Prioritization Model
The Challenge
“Organizations are very immature in resource management. Over 74% of organizations are at Level 1 or 2 in resource management maturity, which means that there are no organizational standards for resource management. Our research further shows that as organizations mature in their resource management practices, in general their organizational performance improves.
- Source: PMI (2008). Portfolio resource management.
The Solution
1- Visibility on resource utilization by department and function.
2- Visibility on which products are utilizing over-capacity function.
3- Dynamic resource utilization analysis.
“Data-driven resource allocation results in 2x return on investment ensuring funding is utilized in the best manner possible, solidifying the profile of the company in the eyes of investors/funders.”
Step 5: Automated Data-Driven Recommendation Engine
Step 5: Automated Data-Driven Recommendation Engine
Step 5: Automated Data-Driven Recommendation Engine
The Challenge
“The area of weakness most commonly cited by respondents (30 percent in total) is Product termination. Similarly, one third of respondents say their firms are too slow to terminate Products that should be ended, and that executives are too reluctant to take action. Thus, respondents believe that 20 percent of current Products in strategic portfolios should be terminated, yet limp on, using up valuable resources.”
- Source: PMI (2015). Implementing the Product Portfolio: A Vital C-Suite Focus.
The Solution
1- Highlighting products that should end.
2- Visibility on resources utilized by products that should end.
3- Visibility on the impact of re-allocating resources to better performing products.
“One of the most difficult decisions is to decide to cancel a Product/product, Automated data-driven Product/product prioritization and resource management recommendation engine saves 80% of executive’s time and makes the decision easier to take because it is based on well-crafted algorithms that took into account different scenarios, maximized portfolio performance, and optimized resource utilization”
Common Question
Step 5: Automated Data-Driven Recommendation Engine
Step 5: Automated Data-Driven Recommendation Engine
Is there one way to implement a PPM practice? Each organization will be unique in the way it implements PPM, However, the core concepts are the same and there are best practices from the global industry that need to be applied
What kind of data repository do we need to implement?
“It can be a PPM software, can be a database/data warehouse, it can even be a process of collecting the data and storing it in one place, as long as the Products/products data need to all be in one place.”
Are there certain models to implement prioritization in a data-driven way?
“There are many, however, the most prominent three are: Decision Tree, Monte Carlo, and Product Scoring.”
What kind of resource utilization do I need to track?
“Resources, mainly human and financial resources need to be tracked in terms of capacity and utilization.”
Do I need to track utilization on a Product level?
“Yes, resource utilization needs to be tracked on the Product level, both in terms of historical utilization and Producted estimates leading up to Product launch.”
Does the recommendation engine eliminate the need of executive discussions?
“Not necessarily, the recommendation engine gives the discussion a set of suggested actions to consider.”
What kind of insights do I expect to have from the automated recommendation engine? “Recommendation engines should give insights based on predetermined criteria, those insights are to best allocate resources leading to the optimization of performance and maximization of earnings/profits.”
There are several ways to achieve this:
Option 1:
Do it yourself or hire a few consultants to set up your project/product portfolio practice and they can attempt to do it in a data-driven way, however, this will likely fail because:
- Consultants that understand Innovation Portfolio are more likely to
hold expertise in their technical fields but lack the business & portfolio management skills.
- Project/Product portfolio management executives that can help set up the governance models lack the analytics and data science expertise.
- The skills needed to set up a data-driven PPM model are so specialized, it will take you at least 12 hours per day for 1 year to become proficient without any help.
Option 2:
You can implement the DDIM Framework and achieve 2x
faster project/product launch and 2x ROI which will be 4
times faster and 4 times cheaper.
How It Works
Before, when you wanted to plan and manage your innovation
projects/products, you would have to plan and manage each project separately.
But now, you can use a simple project/product portfolio management model to launch projects/products 2x faster with higher performance and profits without wasting time, energy or resources.
Do you see how easy that is?
Before, when you wanted to look at the entire innovation project/product list, you would have to go around asking each project/product manager for information.
But now, you can use this simple project/product portfolio pipeline data repository to achieve alignment among stakeholders and decision-makers which leads to 2x resources utilization without the frustrations of wasting time, effort, and resources.
Do you see how easy that is?
Before, when you wanted to make decisions on
project/product prioritization, you would have to make
subjective decisions that anyone can challenge.
But now, you can use this simple data-driven project
prioritization model to 2x return on investment
without losing valuable resources or missing
high-growth potential opportunities.
Do you see how easy that is?
Before, when you wanted to make a decision on
allocating resources, you would have to allocate
resources based on subjective decisions.
But now, you can use this simple data-driven resource
allocation model to 2x return on investment without
wasting resources.
Do you see how easy that is?
Before, when you wanted to get insights to use in
project/product prioritization and resource management
discussions, you would have to spend days sifting through data
and metrics, and eventually not be sure that you have the best
scenario.
But now, you can use this simple automated data-driven
recommendation engine to save 80% of high-valued executive
time and know that all different scenarios have been
considered without wasting time or second guessing your
insights.
Do you see how easy that is?
CAse studies
—Pauline Lim from gsk
— Raghu Sethuram from Pfizer CH
— Raghu Sethuram from Pfizer CH
“On a personal level, you gave me back 30% of my time. And on a company level, you helped us see a two fold increase in our innovation pipeline value which is worth about $75M.”
— Raghu Sethuram from Pfizer CH
— Raghu Sethuram from Pfizer CH
— Raghu Sethuram from Pfizer CH
“Working with you saved 80% of my time and increased innovation pipeline value by 5-10% which is worth about $60M”.
— Sherif Desouky from GP TECH
— Raghu Sethuram from Pfizer CH
— Sherif Desouky from GP TECH
“We should write a book describing this innovation management system”.