Editor’s Note – Connecting Dots

By: JoDeen Urban, Editor In Chief, The Source

Associating ideas or discovering unique insights after sifting through pools of data has become significantly more complex in the Age of Big Data. When the puzzle “join the dots” was created, its premise was to use our visual memory to discern what the picture should look like as we expectantly drew a line from dot-to-dot. Until recently, “connecting the dots” to unearth business intelligence and innovate using customer experience data and other analytics to layer and frame ideas was an appropriate metaphor – although it relied more upon deductive and abstract reasoning than using the “mind’s eye”. We could improve upon existing processes and develop product or service enhancements through new factual interpretations or twisting and stretching concepts into new shapes. Sometimes, the Big Idea was also born.

But, big data and SMAC technologies (Social Mobile Analytics and Cloud) have ushered in an entirely “new normal”. Seemingly ordinary minutiae of unfathomable quantity can now be hyper-digitally churned in mind-bending ways to yield disruptive power on a scale never before experienced. Industries are challenged with the prospect of either disrupting or being disrupted by this environment.

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In our world of sourcing, delivering multisourcing services and data analytics capabilities to support the needs of companies to remain competitive, pursue innovation and drive change means connecting all the dots – seen and unseen. Our mind’s eye and cognitive systems are forced to morph. In order to exploit digital breakthroughs we are adapting sophisticated neuroscience and anthropological architectures. It’s not child’s play anymore.

The digital disruption has forever altered the way we think, create, problem solve and conduct transactions. This month’s issue presents sourcing perspectives on this theme from different vantage points – innovation, global drug discovery, predictive data analytics and contractual partnerships. How successfully we blend facts and predictors will always be heavily influenced on how well we continue to underpin our new knowledge on core values. Integrity, trust, collaboration and accountability to one another are the four cornerstones that must remain inviolate. Existing best practice, compliance and accountability rules may have a shorter than expected lifespan. Governance practices and standards that can be continuously adapted against a landscape that is exceedingly fluid are critical.

Delivering multisourcing services and data analytics to support the needs of
companies means connecting all the dots – seen and unseen.

Scott Schlesinger, SVP and head of Business Information Management at Capgemini recently remarked to Outsourcing Center: “Jumping in to analyze large volumes of diverse data without first having a true business use case and some level of governance in place…is a recipe for disaster. You have to create a strong control framework so you know that the data you’re analyzing is good; that your models are sound, and that your processes adhere to privacy standards, which vary from country to country. Big Data analytics is such a hot topic that it’s easy to get caught up in technology.” Click here for the referenced article.

A different mindset is required for making outsourcing decisions in this atmosphere. The complexity of demands made upon all supply chain segments is on the rise. Pricing, capabilities and performance metrics are increasingly connected to the ability of suppliers and vendors to provide data science skills in support of their customers’ digital analytics transformation. Add to this Sustainable and Socially Responsible Sourcing which is embedding itself, rightly, into the terra firma of global business. Keeping all of this moving in an ethical and profitable direction requires evolving our competencies and imagination so that we can construct new pictures from dot-to-dot-to-vectors and beyond.

We welcome contributors to this publication. Please share your insight and opinions at contactGSC@gscouncil.org, or contact me directly at jodeen@gscouncil.org.

JoDeen Urban
Editor In Chief

JoDeen is an independent management consultant working with established companies as well as start-ups on strategy, organizational capability and business model innovation.


Global Drug Discovery Outsourcing Market Gaining Momentum

Zhang, J.By: Jim Zhang, President, JZMed, Inc.

Today, externalization has become a core strategy among pharmaceutical and biotechnology companies for all types of activity, including R&D and manufacturing. In fact, the original concept of outsourcing has now been expanded to include all types of collaboration, including partnership and technology licensing.

Drug discovery has been one of the core sectors of the long value chain of drug R&D. However, in recent years, almost all major pharma and biopharma companies have focused on developing late-stage drug candidates due largely to the global financial crisis and the pressure of patent expirations of blockbuster drugs. Drug discovery research has been less focused, with many companies primarily relying on external resources, including R&D-focused biotech companies and professional discovery research service providers (CROs).

Outsourcing of a variety of tasks has become a
core strategy among pharma and biopharma companies.

This focus on late-stage development is now making many large pharma and biopharma companies realize that their early-stage pipelines have become thin. Drug discovery research has, thus, recently regained focus among these companies. However, their research strategy in this field has changed significantly.

New Strategies for Drug Discovery Research

New R&D strategies are constantly evolving in global pharmaceutical and biopharmaceutical industries. All drug companies have now recognized that early-stage drug discovery is not just for identifying a new medical (either chemical or biological) entity for a target. Rather, it is about validating the identified therapeutic target and better understanding the disease biology, pathology, and interactions between the compound and the target (as well as those off-targets). Consequently, major pharma and biopharma companies are more focused than ever on understanding disease biology in order to have more accurate therapeutic targets and to employ new technologies to truly improve R&D success rates.

Photo courtesy of Research Optimus

Photo courtesy of Research Optimus

New Drug Discovery Outsourcing Strategies

Along with the change of their discovery research strategy and practice, major pharma and biopharma companies have been shifting their outsourcing strategy from a risk-sharing emphasized model to a more technology-concentrated partnership. Discovering new therapeutic targets and thoroughly validating them have become the new priorities of drug discovery research. The integrated drug discovery outsourcing model has become the prevailing trend.

To this end, drug companies need the involvement of academia in early drug discovery more than ever. Almost all global major pharma and biopharma companies have forged close partnerships with a number of academic research institutions in recent years. Moreover, they are increasingly integrating human genetics research into their discovery and development programs. Genomics and proteomics have been widely employed not only in drug development, such as for the development of companion diagnostics and patient stratification, but also in drug discovery, such as for target identification and validation, safety biomarker development and application, and development of novel antibody drugs. In all these R&D activities, academia is playing increasingly important roles.

The new outsourcing strategy also is creating broader collaborations, not only with peer competitors, technology-bearing biotech companies, and professional outsourcing service providers, but also with academics, for both drug discovery research and new therapeutic target identification and validation. The latter includes not only pure research on disease biology but also discovery and validation of new biomarkers and their applications. Indeed, academia has become the third key element of many companies’ R&D efforts.contractsourcingfig1

Emerging Countries Play Increasingly Important Roles

Until now, the most desirable technology in drug discovery research has been compound libraries with diverse structures. However, this type of R&D work, especially the construction of small molecule compound libraries, has now been considered to be approaching maturity. Few drug companies large or small are now willing to assemble a large, internal team of synthetic organic chemists to do it. The majority has, instead, been outsourced in recent years to China and India as well as emerging countries. These outsourcing destinations have been the main places for global drug companies to look for focused compound libraries of small molecules that possess diverse structural features.

Continued growth in the global drug discovery outsourcing market is
expected to grow as means to improve R&D efficiencies and productivity.

On the other hand, there are growing numbers of service companies in emerging outsourcing destination countries such as Brazil, Russia, and Ukraine that are now also able to offer integrated drug discovery research services. Multinational drug companies are thus expanding their discovery research outsourcing scope in these countries while strengthening their current relationships with local partners.

Future Growth Potentials

According to research conducted by JZMed, Inc., in the past few years the global drug discovery outsourcing market has been growing at a CAGR of about 10.5 percent. Its current market size is estimated at $13Bn, accounting for close to 10 percent of the current total global drug R&D spending.

Of the total market value, the small molecule drug discovery outsourcing service market accounts for about 87 percent, reaching about $11.25Bn. Between 2009 and 2012, its CAGR was around 11 percent. The current biologic drug discovery outsourcing market is estimated at only about $1.75 Bn, accounting for about 13 percent of the current total global market. However, its CAGR from 2009 to 2012 was about 37 percent.

The current average outsourcing penetration of small molecule drug discovery research among major companies is estimated at 40 percent. The current average outsourcing penetration of biologic drug discovery research is, however, only about 15 percent. The overall average drug discovery research outsourcing penetration is about 30 percent at present.

Nearly half of the global drug discovery research
will be performed by third parties by 2018.

Driven by the strong desire of all drug companies to improve efficiencies and productivity in their R&D efforts, the global drug discovery outsourcing market is expected to grow at a decent pace in the foreseeable future. JZMed, Inc. forecasts that the global drug discovery outsourcing market will likely experience a CAGR of about 11.5 percent between 2013 and 2018, and its market value will likely reach close to $25Bn by 2018. By then, the overall industry-wide average outsourcing penetration of drug discovery research will likely reach close to 49 percent. In other words, nearly half of the global drug discovery research will be performed by third parties by 2018.

Of the total global market, the small molecule drug discovery outsourcing will likely account for about 75 percent reaching close to $19Bn by 2018. Whereas the biologic drug discovery outsourcing will likely account for about 25 percent reaching more than $6Bn by 2018 (See Figure 1).

About the Author: Jim J. Zhang, Ph.D., is President and Managing Director of JZMed, Inc., a leading market research company that specializes in the research of global pharmaceutical outsourcing industry with emphasis on China, India and emerging markets.

Before founding the company, Jim worked for nine years with Albany Molecular Research, Inc. (AMRI), a US-based and currently one of the world largest CROs. Jim’s technical expertise spans from chemical process research and development to drug discovery and development for viral infection, cancer, chronic obstructive pulmonary disease (COPD) and cystic fibrosis. Currently he holds 18 patents and is the principal author of 12 peer-reviewed research articles.

This article was originally published by Life Science Leader.com on July 1, 2014. It has been annotated and reprinted with permission by the author. Facts within the are partially based on the latest research report of JZMed, Inc: “The New Trends of Global Drug Discovery Outsourcing.”

Trust and Collaboration: McDonald’s Supply Chain Strategy

Vitasek, K.100x100By: Kate Vitasek, Author, researcher, educator and innovator of the Vested®business model.

It’s apparent that for strategies to be taken seriously involving Supply Chain Management (SCM) and Business Process Outsourcing (BPO) a company’s Corporate Social Responsibility (CSR) plan must be an integral part. All of the moving parts must work together in an ethical and socially responsible way.

This is especially true for service provider, IT outsourcing and supply chain relationships. Just look at the huge and ongoing work regarding human and labor rights that the apparel and footwear industry is doing to correct unsafe, low-pay, sweatshop conditions that have come to light recently in countries such as Bangladesh, Vietnam and China.

Driven by globalization, supply chains are rapidly evolving and gaining in complexity across every industry sector, and the vendors in those supply chains are often a moving target as multinational corporations search for low cost suppliers. Concerns also center on how labor standards and working conditions can best be monitored and enforced throughout the chain.

These are business processes and serious issues that CSR plans must account for clearly and realistically. Fortunately, there is good news: companies are catching on to the fact that their supply chains must be anticipatory, adaptive and environmentally aware to be sustainable. They know that suppliers need to be brought into the corporate sustainability discussion in real ways, not just as P.R. frosting.

They must do CSR right and would do well to emulate the approach of companies who employ the Vested® shared principles of trust, collaboration and flexibility. McDonald’s is one case in point.

Suppliers need to be brought into the corporate
sustainability discussion in real ways, not just as P.R. frosting.


“From my perspective, the heart of an outstanding supply chain is trust and transparency, features that contribute to natural resilience and provide a level of nimbleness not possible in more guarded systems,” says Kurt James, V.P. of supply chain, McDonald’s Japan.

James said the McDonald’s supply chain is designed to be “efficient, adaptive and collaborative,” traits that have enabled the company to enter new markets at a scale and pace that is unmatched by its competitors. “We talk about the supply chain at McDonald’s as a shared system, rather than as our system. This mentality of joint ownership allows us to work as one efficient organization with our suppliers, planning for the future and adapting to the present in a cohesive and integrated way,” James adds.

Traditional supply chains can crack under the pressure of unforeseen political, environmental, or competitive changes, but the McDonald’s “three-legged stool” philosophy and cooperative approach can absorb the shocks produced by the unforeseen while quickly adapting to frequently changing demands, specifications, and volumes. James said it’s flexibility and resilience based on trust.

McDonald’s deeply-ingrained culture for long-term, win-win relationships with suppliers dates back to its inception, when founder Ray Kroc established a culture of trust and loyalty.

In May McDonald’s issued its “Best of Sustainable Supply 2014,” which honored 36 suppliers and 51 projects that “represent real innovation toward a more sustainable supply chain.” McDonald’s received 585 submissions, nearly 40 percent more than for the previous “Best of” report.

McDonald’s executives and industry experts recognized sustainable accomplishments across eight platforms: Climate Change and Energy; Water; Waste; Land and Biodiversity; Human Health and Welfare; Animal Health and Welfare; Community Impact and Economics.

Photo courtesy of Institute for Human Rights and Business

Photo courtesy of Institute for Human Rights and Business

“Innovation is key to our CSR and sustainability journey, and McDonald’s suppliers have an impressive track record of innovating for what we call sustainability’s three Es: ethics, environment, and economics,” said Jose Armario, executive vice president, McDonald’s Global Supply Chain, Development & Franchising. McDonald’s approaches supply chain management through the three Es—and they are the theme of McDonald’s 2012-2013 corporate social responsibility & sustainability report: “Our Journey Together For Good.”

“We are committed to working toward a tomorrow where quality food and balanced choices are accessible and affordable to all. Where the food we serve is sustainably sourced from thriving farms. Where environmental protection and efficiency are universal. Where people from all walks of life are valued for their unique contributions to a shared global community,” says Don Thompson, McDonald’s president and CEO, in the report.

These are not mere words:

  • 100 percent of the fisheries that McDonald’s sources whitefish from are verified sustainable.
  • 99 percent of supplier facilities signed the company’s Supplier Code of Conduct.

Sustainable sourcing is vitally important to McDonald’s and its supply chain. The CSR report says: “By sourcing our ingredients and packaging sustainably, we aim to create value for our business and society. We are committed to doing what we can to help protect oceans and other valuable ecosystems, promote resource efficiency, and support the economic viability of farming, fishing and responsible land management so that resources are adequately available for generations to come.”

In addition, the company oversees the three Es at each level of its supply chain: raw material production, processing, and distribution. “Among other things, this means working with suppliers to innovate and implement best practices for sustainable ingredients, requiring that our suppliers protect human rights in the workplace, and safeguarding food quality and safety through best practices in animal health and welfare.”

Innovating sustainability’s 3-E’s:
ethics, environment, and economics.

Steps that McDonald’s has taken to strengthen supply chain sustainability, include partnerships with nongovernment organizations (NGCs), a Supplier Code of Conduct, and increasing supplier capacity in emerging economies. It has initiated supply chain goals and protocols for measuring, identifying and scaling sustainable beef production; sustainable logistics through system-wide continuous improvements in logistics efficiency, including the increased use of biofuels; promoting environmental best practices at supplier facilities through a Global Supplier Performance Index and the Supplier Code of Conduct.

  • The Performance Index tool includes corporate social responsibility and sustainability—along with innovation, contingency planning, business strategy and other topics—and helps McDonald’s evaluate suppliers on a variety of measures including environmental, social and other metrics. This helps clarify what is meant by CSR & Sustainability leadership. The formal evaluation, which takes place every 1 to 3 years, is complemented by quarterly reviews.
  • The Supplier Code of Conduct is the cornerstone of McDonald’s Supplier Workplace Accountability program and sets clear guidelines that help suppliers understand its expectations and how to live up to them. Every supplier is required to sign the Code. In November 2012, McDonald’s launched an enhanced Supplier Code of Conduct, the result of a two-year process that included benchmarking with a number of organizations that lead in this area, consultation with external experts in supplier workplace accountability, a human rights gap analysis and dialogue with suppliers.

The resulting system is one of unparalleled connection, collaboration, and mutuality. What is noteworthy along the McDonald’s CSR path is not sustainability goals this year or next, and what the companies can do by themselves: it’s about sharing vision and collaboration to achieve a long-term culture of sustainable social and environmental change—and how they go about it with their partners.

About the Author: Kate Vitasek is an international authority for her award-winning research and Vested® business model for highly collaborative relationships. Her work has led to five books, including: Vested Outsourcing: Five Rules That Will Transform Outsourcing, and Getting to We: Negotiating Agreements for Highly Collaborative Relationships.

A faculty member at the University of Tennessee, World Trade Magazine named her as one of the “Fabulous 50+1” most influential people impacting global commerce.


Big Data – Big Questions

Karen MorrisBy: Karen A. Morris, Board Member, The Global Sourcing Council and Chair, GSC Women’s Empowerment Committee

The COO of a global firm recently asked me a right question and an important question. The right question is this: “In 2014, what kinds of conversations should we be having about big data?” The important question is this: “Is big data a big innovation?” The latter question yields to an easy answer. Yes. Big data is potentially the most significant digital-era innovation. Bigger than the internet. A big conversation then?

Innovation and big data share a common problem. We talk about them often but may not necessarily appreciate what they mean. My minimalistic working definition of strategic innovation is the creation or extraction of new value from insights. Coincidentally, that definition also captures what big data uniquely enables – previously unattainable insights, the energy source of innovation and competitive advantage. Big data is more than big. We are talking about almost incomprehensibly large amounts of data. A zettabyte is a trillion gigabytes, or a 1, followed by 21 zeroes. IDC Digital illustrated this simply – should you fancy storing a zettabyte on 32-gigabyte iPads, you would need 86bn devices.

Big data is potentially the most significant digital-era innovation.

Beyond and because of this massive scale, big data implies the possibility of navigating those oceans of information to discover meaning, find patterns and surprising connections. A mere decade ago, 25% of stored information was digitalised – now it’s tipping past 99%. In innovation terms, this is jaw-droppingly amazing. Not even 3D printing can vie with big data’s draconian force as the innovation that keeps on innovating – and its potential is still nascent.

Big data can wield its innovative prowess on the least tractable of mankind’s challenges. Demonstrable impact is emerging in all branches of science, in healthcare, in disease control, in pollution and climate change.

It is transforming business behaviours, operations and business models. In the insurance industry, for example, part of the yield on big data at the enterprise level happens to be risk mitigation – or even elimination. So big data elevates insurers’ abilities to understand and manage risk of almost any genre. The conversation we should be having in 2014, with some urgency, is whether the historically data deploying insurance industry is set to be revolutionised, to disrupt or be disrupted by big data. If not, from what does it, or other industries, derive this immunity?

Graphic courtesy of University of North Carolina - Charlotte

Graphic courtesy of University of North Carolina – Charlotte

What we use innovation for matters. It is depressing, if unsurprising, that some commercial big data applications are consumer manipulations disguised as consumer centricity. Big data concentrates immense and dangerously ungovernable power in the hands of a few. In the wrong hands – terrorist, criminal, governmental – everything good can be put to sinister use. Our big data business conversation cannot evade its social, philosophical and political relevance and risks, however daunting. Our conversation should also appreciate recent realisations of big data’s independent economic value, distinct from the functional purpose that first created it. Moreover, big data’s value is not depleted but expanded by use and reuse. This demands a major mental shift; historically data’s value, unless IP or specifically exploitable, derived from their ancillary support to a business function.

Big data’s value is not depleted but expanded by use and reuse.

Big data occupies a lead, not supporting, role as a strategic asset. Such attributes distinguish big data from the more traditional use of data— capturing data in production and archival systems, deploying historical data in myriad ways enhanced by analytics from process improvements to product development, segmentation and so on. We will need to be cautious not to conflate or even see as linear what we did with data before big data and what happens next.

What happens next goes to the heart of big data’s story and our own human story. Big data will transform the way we live, work, and think. So we must ask questions in thoughtful, inclusive conversations. Our leadership and global citizenship challenge is to co-author the story of what happens next.

The swift and the strong may win the short-term race to harness big data tools, but the uniquely human challenge in the long run will be to figure out where intuition, ingenuity, common sense, instinct and error belong in our brave new world.

About the Author: Karen Morris is a strategic advisor to national and multinational companies. She is also a frequent speaker and writer on innovation and leadership at global forums and conferences around the world.

Data Science and Analytics: Outsourcing Optimization

Kalakota R100x100By: Ravi Kalakota, Partner at LiquidAnalytics

If you’re an executive, manager, or team leader, one of your toughest responsibilities is managing and organizing your analytics initiative.

The days of business as usual are over.  The cost of data generation is falling. The cost of collection and storage is also falling.  The speed of insight-to-action is increasing. The bottleneck is clearly shifting from transaction processing to Analytics & Insight-driven Action.feldframework_why

Here are just a few examples of analytics at work:

What is Data Science? 

“Data Science” is an umbrella term that encapsulates the extraction of timely, actionable information from diverse data sources. It covers data collection, data modeling and analysis, and problem solving and decision making. It incorporates and builds on techniques and theories from many fields, including mathematics, statistics, pattern recognition and learning, advanced computing, visualization, and uncertainty modeling with the goal of extracting meaning from data and creating data products.

Data science is often used interchangeably with business analytics, although it is becoming more common. Data science seeks to use all available and relevant data to effectively tell a story that can be easily understood by non-practitioners.

Data science is nothing new. But digital has increasingly created new opportunities where scientific methods can be applied to massive, real world data sets.

What are Some Areas to Outsource?

The different areas of data sciences or analytics outsourcing (based on lifecycle of a project) include:

  • Analytics Consulting (strategy, platform selection, model development, decision process re-engineering).
  • Analytics Platform Deployment, Customization and Integration.
  • Analytics “as-a-service” platform strategies – by leveraging a common set of development, production, and support capabilities.
  • Analytics Program Staffing – resource augmentation (salary and intellectual arbitrage), project and program management.
  • Domain and Function Modeling Knowhow – depends on how and to what degree the tasks and KPIs are standardized.
  • Legacy BI modernization – a growing problem of enhancing or wrapping the old to produce new.
  • Emerging technology areas like Mobile BI…using an “innovation-as-a-service” model.
  • Data Quality – with data increasingly critical to business strategy, the costs of poor quality data, fragmentation, and lack of lineage take center stage.

For each area and business need (transformation vs. strategic vs. tactical) there are different vendors that are a better fit.  Most of these firms are evolving their capabilities but are rooted in providing BI and Analytics capabilities on a staffing or project basis.

Outsourced analytic providers serve many industries, including retail, telecommunications, healthcare; and others provide clients with domain expertise in database-driven marketing and customer segmentation.

Who are the Industry Leaders in this Space?

This is a tough question to answer without more context around problem or use case.  But in general, a survey conducted by LiquidHub of market leaders shows:

  • Broad “super market” services firms with a broad array of capabilities – Accenture, IBM, Deloitte.
  • The growing pure-play analytics firms include: Mu-Sigma, Opera, EXL Analytics.
  • Offshore vendors who have built their model around analytics – Genpact (spin-out from GE).
  • Domain specific vendors — Dunnhumby (retail analytics); Acxiom (database marketing).

Increasingly vendors are able to offer horizontal and vertical solutions effectively packaged in a variety of configurations. Vendors are becoming more sophisticated as they gain experience handling large, complex datasets. The services range from Data Sciences -> expertise in various techniques -> toolsets -> vertical specific expertise.

Issues to Consider in Picking an Analytics Service Provider

  • Who handles the data?; How sensitive is the data?; How unusual (and competitive advantage based) are the analytics? These questions usually dictate the engagement model.
  • Capability of the team: most firms and vendors are capable of report generation, descriptive statistics or dashboard generation.
  • Ability to analyze and interpret results: moving to more complex predictive models requires domain expertise and use case knowhow…most vendors claim to have this but very rarely do.
  • How easy are they to work with? Do you have to spoon feed them or is ambiguity ok? Since clients are looking for faster turn-arounds for more sophisticated insights on continuously increasing amounts of data, vendors need to deliver solutions that will scale better with lower cost of ownership to meet their clients’ internal service-level agreements.
  • Experience with large complex data sets or ability need to mix and match different types of data.
  • Emerging technology expertise – can they help innovate around new data sources like mobile or hyper-connected “Internet of Customers”?

Different Resource Cost Models

  • Onshore consultants (data scientists will be in the $250-350 per hour range). Specialized domains (Risk Analytics) will carry a 30% premium ($300-$600 per hour fees).
  • Hot geographic areas with a lot of startups like San Francisco or New York – the rates may be much higher….supply vs. demand.
  • China, especially Shanghai, is a good place for analytical talent in my experience. India is also a good location with different Indian Statistical Institutes (where sound engineering firm Bose came from) also has good cheap talent.  At LiquidHub we built an actuarial center of excellence in New Delhi which worked well.
  • Offshore analytics consultants (India will be around the $30-$75 per hour range – pay premium only for IIT and IIM educated personnel; Indian Statistical Institute (ISI) also generates good graduates).

Resource costs depend on domain expertise and analytics niche. Niches include: Predictive analytics; Behavioral analytics; Risk analytics; Sales & Marketing analytics, Social Media analytics, or Web analytics.

Different Pricing Models in Analytics Outsourcing

The structure of the pricing for the outsourcing contract can be one of the following:

  • Cost Plus. This approach pays the supplier for its actual costs, plus a predetermined profit percentage. This plan allows little or no flexibility when business objectives and technology change during the life of the contract, nor does it give any incentive for the supplier to perform more effectively.
  • Unit Pricing. This is a set rate determined by the supplier for a particular level of service, and the client pays based on its usage. Paying for desktop maintenance based on the number of users is an example of this approach.
  • Fixed Price. Some buyers think this is the best approach, because they know exactly what the supplier’s price will be, even in the future. But the problem with this approach is that if the buyer does not adequately define the scope of the process and design effective metrics before signing the contract, too often the result will be that the supplier claims a particular service or service level is beyond the scope of the contract and then charges a premium for it.
  • Variable Pricing. This plan involves use of a fixed price at the low end of the supplier’s service, with variances based on higher service levels. Its effectiveness, again, depends on adequately defining scope of process and metrics.
  • Incentive-based (or performance-based) pricing. Here, the buyer provides incentives to encourage the supplier to perform at peak level (or complete a one-time project ahead of time, for example) by offering a bonus reward if the supplier performs well. This same plan works in ensuring that the supplier must pay a penalty if it does not perform to at least the “satisfactory” service level designated in the agreement. This plan is the one to use to ensure the supplier’s excellence in performance.
  • Risk/reward sharing. The buyer and supplier each have an amount of money at risk and each stand to gain a percentage of the profits if the supplier’s performance is optimum and achieves the buyer’s objectives.

The buyer will select a supplier using a pricing model that best fits the business objectives the buyer is trying to accomplish by outsourcing.

The Measures of Success

  • Effort based vs. Outcome based
  • For repeated analytics like dashboard generation – one can have SLA, Quality and Errors as a measure of success.

How Effective are Vendors in Scaling?

  • Depends on whether the vendor is an IT vendor like TCS, Big 5 like Deloitte or pure-play analytics vendor like Mu-Sigma. These vendors can ramp-up from a standing start to 200 people in a few months.
  • For simple use cases and simple analytics – most vendors can ramp up to 30-50 people easily (made up of data management, cleansing/quality, BI report generation and dashboards).
  • Vendors can also ramp up around technology platforms like SAP and Oracle more easily than around use cases like marketing analytics.
  • For more challenging use cases like recommendation engines, the next best offer which requires more sophisticated modeling (simulation, optimization, time series etc.) – most vendors probably can assemble a small team but may not be able to scale easily beyond 10.
  • Domain modeling expertise – architects and skilled project managers tend to be the hardest skills to find.

The Expected Benefits of Analytics Outsourcing

  • Specialization, Focus, Speed-to-market and Scale tend to be the expected benefits.
  • Vendors may have proprietary IP and tools.
  • Lower cost by leveraging economies of scale (often the sales pitch but seldom works in execution).
  • Better process quality through forced standardization (vendors force clients to standardize which requires re-engineering the way things are done).

Firms must not expect to outsource analytics and then just assume that the specifics will take care of themselves. This is a recipe for disaster. Managers must retain enough program management capability to enforce processes, communicate with all parties, and keep track of critical details.

About the Author: Ravi Kalakota Ph.D, is a Partner at LiquidHub, a digital integrator with operations in North America, Asia, and Europe. He has over 20 years of experience as a global CIO, CTO (for Mercer – the Health, Retirement, Talent and Investment consulting services firm of Marsh & McLennan Companies); Managing Director with Alvarez & Marsal Business Consulting, a premier restructuring and performance improvement firm; and as CEO for several technology research and consulting firms.

Ravi has co-authored 10 books on e-commerce, e-business, mobile, web services, and global outsourcing, including Offshore Outsourcing: Business Models, ROI and Best Practices and Global Outsourcing: Executing an Onshore, Nearshore or Offshore Strategy.

For more detailed descriptions and vendor listings for Data Science and Analytics Outsourcing – Vendors, Models, Steps see Ravi Kalakota’s blog at: http://practicalanalytics.wordpress.com/2013/11/06/data-science-and-analytics-outsourcing-vendors-models-steps/