Introducing the Proof of Value program for Advanced Analytics

by Alan Herrera, Sr. Product Marketing Manager for Advanced Analytics and Proof of Value Program Lead

In recent years, the promise and, in some cases, the hype of big data have produced plenty of critics who doubt the benefits of big data or point to the potential pitfalls organizations face when engaging in big data and analytics projects. Although these critics make some valid points (e.g., not every organization has big data or needs to manage and analyze big data), a more pragmatic approach is to look not just at big data but also at small data, long data, dark data, and any other metaphor for real data — in other words, all data.

So why should we care about data? IDC recently conducted research commissioned by Microsoft that showed better outcomes from data and analytics projects correlating with greater competitiveness of an organization in its industry or a better ability to fulfill its mission in the public sector. Although correlation does not equate to causation, a growing body of research shows financial and productivity benefits directly linked to better data-driven decision making enabled by business analytics solutions. IDC’s research found that companies taking advantage of their data had the potential to raise an additional $1.6 trillion in revenue by 2017, IDC called this the data dividend (source IDC April 2014).

One of the most effective ways an organization today can leverage their data is through machine learning. Machine learning enables business to move beyond the “what happened” of traditional BI to the “what will happen” insights enabled by predictive analytics. Predictive analytics delivered via the Cortana Analytics Suite (CAS) can translate past data and human input into deep statistical analysis, potentially uncovering patterns in the data and insights on business drivers that will drive improvement in the underlying business. In short, machine learning enables businesses to drive tangible return on investment. With CAS our customers can create solutions across a number of scenarios, such as customer churn analysis, fraud detection, targeted advertising, predictive maintenance and more.

Why Microsoft?

Microsoft has been using machine learning internally since 1992, with the founding of Microsoft Research. An early example is the use of machine learning to improve Hotmail spam detection. We then went on to optimize Kinect Functionality for Xbox. More recently, we used natural language algorithms with Skype Translator to enable real time translation.

With the availability of Azure Machine Learning, we have the ability to offer these kinds of solutions to our customers at scale. Our vision with Azure Machine Learning is to make Advanced Analytics accessible to everyone. We provide a modeling experience that welcomes all skill levels. Data scientists can use trusted algorithms from Xbox and Bing, without writing a single line of code and more seasoned data scientists can mix and match with Python and R built in, or even drop in their custom code. The tool speaks their language. Then, we can deploy in minutes as a web service. The one-click deployment is what makes our product so unique.

Cortana Analytics Suite users can deploy their solution to the community through the in-product Gallery and learn best practices for their own solutions. They can then take it a step further with global scale through the Azure Marketplace, where partners can brand and monetize their solutions and developers can access them, with no data science skills needed. The data science is inside.

How to partner with Microsoft

Over the past year, our Data Science Team launched a unique new program called Proof of Value. The program allowed our customers to leverage the skills of our best Data Scientists to develop Advanced Analytics solutions in a span of 2–3 days. Through this program, we have worked with many industry leaders to help create solutions to improve their business. With the proven success of this program and the upcoming launch of CAS, Microsoft is inviting you to join in on this exciting opportunity.

Program overview

The goal of a Proof of Value engagement is to scope and deliver an Advanced Analytics solution in an accelerated time frame. Step 1 is to identify customers who have a well-defined business program and determine if the issue can be addressed with Advanced Analytics. This is followed by work to determine specific success metrics for the solution. These success metrics will help the customer understand the impact of the solution and will help the Microsoft partner to position the value of the solution in tangible terms. Proof of Value metrics typically fall into the following three categories:

  1. Return on investment: What is the value off success vs. doing nothing?
  2. Productivity downtime: How much will the solution help reduce downtime costs?
  3. Customer experience: Will the solution improve the customer experience and help retain or acquire customers?

The output from an Advanced Analytics engagement falls into two categories:

  • Initially, a working POC that can be scaled out through a longer-term SI engagement
  • Longer term, an operational solution that will drive Azure consumption

If the Proof of Value (POV) focuses on scoping a future SI engagement to develop a solution, but does not deliver a POC or working solution, it’s not really a POV. Delivering a working POC or operational solution is a critical output.

Program structure

We have scoped the program to require a minimum time commitment from our partners on site with the customer, but any successful engagement will require time ahead of the onsite session to scope and plan for the engagement as well as time to follow up afterwards.

Program length: 2.5 to 3 weeks total engagement time

  • 1 week of planning to identify and sample data sources and determine success metrics for the solution
  • 2–3 days on-site with the customer to build a solution in partnership with the LOB leader who owns the solution and their data science team and/or IT support team
  • 1 week post-engagement support to ensure operational solutions are working as expected, to provide any necessary follow up training and plan and scope any additional SI engagement necessary to operationalize a POC.

Program value to partners

Microsoft is deeply committed to delivering technology that enables broad consumption of Advanced Analytics and the value this brings to our customers. With Cortana Analytics Suite, we will broaden accessibility to machine learning and in doing so, grow the addressable market for advanced analytics solutions.

Partners that join this program will have the ability to share in this growth with Microsoft and build strong practices focused on Advanced Analytics. Benefits will include dedicated readiness for the program and the opportunity to receive leads directly from Microsoft, along with additional resources to help our partners drive successful customer engagements and grow their Advanced Analytics business. We are in the process of planning the readiness and on-boarding activities for the program and will share full details in the coming weeks. 

SI partner status (draft criteria)

Onboard Active


  • Access to data science resources
  • Monthly state of the business report


  • Access to US Partner AA Yammer site and resources
  • Monthly community calls

Access to customizable collateral


  • Identify and submit 3 prospects
  • Marketing plan
  • Opportunity reporting in PSX


  • Access to engineering community support, with qualifying criteria
  • Leads from Microsoft
  • Co-marketing funding available through Hero Makers program

How to join

If you’re ready to join the program, sign up for our Advanced Analytics Partners group on the US Partner Community Yammer network.


  • Join the Cortana Analytics partner site (sign in with your MPN ID is required). The site features information on funding, offers, and incentives, as well as on-demand technical and sales readiness
  • Attend a regional Cortana Analytics Workshop (announcement on timing and location coming soon)

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