Recipe for building successful, scalable analytical capabilities
The secret sauce for incubating analytics centers of excellence that deliver best-in-class solutions and create sustainable value for business.
By (left to right) Rohit Tandon, Arnab Chakraborty and Manav Shroff
With more than 10,000 analytics practitioners solving a wide range of complex business problems, India has evolved into a major hub of worldwide analytics. In the September/October 2011 issue of Analytics magazine, we provided an overview of the analytics journey in India (click here). Indeed, analytics has evolved as the differentiator between companies to make better and faster decisions in the marketplace. Thousands of analytics practitioners across India are helping businesses around the globe in analyzing structured and unstructured data, mine the data to spot hidden trends, predict outcomes and eventually drive profitable interactions with customers, suppliers and partners.
In this article, we will focus on the various important aspects organizations need to consider in developing successful analytics capabilities in India.
India has emerged at the forefront of driving analytics for some of the largest companies in the world. Over the last 10 years, India has gained significant momentum and scale to evolve as the location of choice for many companies for cost-effective and impactful analytical solutions. We can draw on several factors from the analytics journey in India to help establish a structured framework for building out a scalable and sustainable analytics center.
This framework (Figure 1) includes various dimensions that are equally important to scale-up a successful analytics hub for a global enterprise. It starts with:
- Establishing a clear strategic intent for establishing the analytics center.
- Investing in practice and capability development.
- Focusing on talent acquisition and development and building the right culture.
- Driving operational rigor to ensure quality control and robust business continuity plans.
- Co-developing the right business alignment and engagement models with the stakeholders.
Figure 1: Key dimensions for setting an analytics hub.
Strategic sponsorship to invest in analytics center of excellence. A new initiative around setting up analytics center needs to be sponsored by senior management with a clear vision of the strategic objective for establishing the center and the return on investment (ROI) that is expected over a three-to-five-year timeframe. Senior management also needs to evaluate whether it is best to build the capability in-house or use a third-party service provider to build the capability.
Organizations need to think through some specific questions (Figure 2) before deciding on the suitable model. If the organization is primarily looking to test the waters and do some very specific niche tasks out of India, then outsourcing to an external vendor may provide the quickest path to building an analytics capability. If the organization has a long-term strategy to build analytics competency that serves its customized needs, then developing an in-house (captive) center will better serve the needs of the company.
Figure 2: Factors to consider for building in-house vs engaging third-party vendor.
While this strategy of captive centers requires the organization to build the capability from the scratch, it does provide significant benefits in terms of management control, customization and protecting its intellectual property, data security and scalability. If the global organization already has a presence in India, this can be an added motivation to setup the analytics center in India as it provides the organization a jump-start from the infrastructure ramp-up and the support-staff perspective.
Along with executive sponsorship for incubating analytics capabilities in India, there needs to be a clear plan of execution with senior management time commitment to review the milestones and remove any bottlenecks to the program. The experience from multiple successful analytics centers in India indicates that active involvement from the top management in the first year can go a long way to drive the much-needed momentum and associated change management to set up the new venture for success.
Practice development to systematically build analytics solutions across selected domains. The analytics industry in India has matured to provide vertical specialization within analytical solutions. Each of the application areas of analytics requires deep subject-matter expertise, technical knowledge and ability to solve problems with customized solutions.
As organizations begin to think of incubating analytics, the management team should selectively identify the key solutions and associated competencies to be developed and deployed across the organization. Focusing on building specific analytical solutions helps in building robust methodologies, tools, talent pool and the ability to deploy these solutions in a scalable manner globally. Global analytics centers in organizations such as Hewlett Packard (HP) over the last seven years have developed very specific solutions as shown in Figure 3. These solutions have been institutionalized across HP’s business units and functions and have helped in elevating HP’s analytical maturity.
Figure 3: Illustrative analytics solution areas.
There are two key factors that the management team needs to evaluate while building these solutions and associated capabilities:
- Assess the ROI by deploying analytics across each of the key organizational functions.
- Assess the critical “expertise” needs for the analytics center of excellence.
For the areas where the ROI for the business is high, the management can make the necessary investment for building the capability and the talent pool.
Talent acquisition and development to hire and develop the brightest talent pool. Hiring the right talent pool is critical to the success of the long-term sustainability of the analytics organization. While hiring the right talent is an arduous task, keeping them engaged and happy is even more challenging. With increasing demand for analytics talent in India, it is important to pay significant attention to the talent development and engagement program for the organization.
Talent acquisition is the most critical aspect to build up a sustainable delivery engine. Having a well-oiled talent acquisition process can be a big differentiator for the analytics center and enable rapid scalability. Organizations need to adopt a multi-pronged strategy (Figure 4) toward attracting the best talent in the industry. This involves:
- Campus hiring: Many reputed institutions in India are well-known for statistics, econometrics, mathematics, engineering and management disciplines. These are the core disciplines that the analytics organizations generally would need to hire from. Typically the campuses fall into two grades: “A” category, or what would typically be the Ivy League equivalent in India; and “B” category, all of the other schools. Depending on the nature of the work and talent required, companies can chose to partner with a mix of “A” and “B” category campuses during their hiring period.
- Internship programs: Most graduate degree courses require students to go through a two-to-three month internship program. It is recommended that organizations should invest in hiring candidates for these internship programs. This provides an opportunity to identify talent early by offering them a pre-placement offer (PPO).
- Knowledge Forums: Companies can organize specific knowledge/ideation forums that invite candidates to present papers in technical disciplines showcasing their thought leadership in the selected subjects. This provides a great opportunity for analytics organizations to create a strong employer brand in universities and also helps to identify key talent and attract them to the organization.
- Lateral Hiring: To build a team, it is critical to hire the right mix of “experienced” (a.k.a. lateral) hires along with campus recruits. This helps in building the right domain expertise and technical leadership. For lateral hiring, Human Resources needs to identify the right external hiring agencies that would source the appropriate candidates as well as utilize the traditional online sourcing channels.
- Referrals: One of the most successful ways of acquiring the key talent is through a robust “referral” program. It is critical for the organizations to build a mechanism that incentivize existing employees to refer the best talent to the organization. This is the also the most reliable and cost-effective form of talent acquisition.
- Contractual Assignments: Some projects require only short-term staffing. Various third-party organizations help companies staff such assignments. The organizations can tie-up with some of these companies as it can be very effective for managing short-term surge assignments.
Figure 4: Analytics talent acquisition strategy.
Talent development is equally important to ensure that appropriate training is imparted to the teams for continued growth of the individuals. Organizations should focus on a few key areas:
- Induction Training: All employees should go through an induction training program that clearly articulates the organization structure, organizational culture and the HR practices and policies. It is imperative that all employees understand the underlying goals, objective, mission and vision of the organization and the role that they are expected to play in the larger scheme of things.
- Job Specific Trainings: Inherently, the analytics industry is a highly technical area and each employee depending on his/her job role may need very specialized training. These trainings can range from: 1) learning applications/tools such as SAS, SQL and SPSS; 2) specific statistical techniques such as regression modeling, Markov Chains, forecasting techniques, etc.; and 3) exposure to functional domains areas such as market research, customer analytics, supply chain analytics among others.
Figure 5: Talent development framework.
These trainings can be imparted through internal experts or service providers who offer trainings in specialized areas such as:
- Differentiated programs for the top performers: Top performers need to be differentiated through specialized programs. The most effective programs that seem to prove: 1) sponsored opportunities to pursue part-time or full-time higher education programs; 2) cross-functional stretch assignments that exposes talent to challenges over and above their day jobs; and 3) short term (6-12 months) international assignments, typically onsite alongside the business stakeholders.
- Rewards and recognition program is also a very important means to recognize people who have gone over and above their call of duty. A well-structured rewards and recognition program is one of the key levers to improving employee morale and motivating them to exceed their expected goals. Design a rewards and recognition program in a way that it motivates and drives a culture of innovation, customer centricity, thought leadership and collaboration.
Operational excellence for the long term sustained success of the organization. Setting up the analytics center of excellence is only the first step toward building a long-term scalable analytics organization. As the analytics center scales up, the paradigm of operational excellence becomes very critical. It rests on three broad pillars (Figure 6):
- Best-in-class delivery model: This is all about organizing the delivery capabilities around key solution areas, using standard tools and techniques across the organization, and using external benchmarks and quality certifications to validate the robustness of internal processes and approach to delivering the solutions to customers.
- Culture of innovation: The innovation quotient in any analytics center can be a game changer and needs to be built very systematically into the DNA of the organization. In order to make “innovation” part of the culture, it needs to be driven by the top management in the organization by including IP development as part of the employee goals, encouraging submission of white papers in both internal and external knowledge forums and gaining recognition in industry forums for technical leadership.
- Robust business continuity plan (BCP): This becomes very important as companies deploy analytics solution to drive business critical decisions. The analytics center needs to plan for unforeseen events such as network and communication failures, non-availability of people due to illness or natural disasters and loss of data. Any of these unforeseen events can risk the analytics deployment and lead to business disruption. Organizations need to plan in advance and create a robust BCP and regularly test it to mitigate the risks. The BCP should encompass back-up planning for analysts, data archiving and recovery, facilities and infrastructure backup, etc. A thorough BCP helps provides stakeholders with assurance that risks from potential disasters have been reasonably mitigated and also ensures a faster and more effective recovery of business operations.
Figure 6: Operations excellence framework.
Strong business alignment to embed analytics into all business decisions. As the analytics center matures it can truly become a converging point where all the key business decisions are enabled. In order to enable a strong business alignment, having the right management team and a well-defined governance structure is critical. The analytics center in India should be closely aligned with the on-site business analytics sponsor to enable good translation of business context. The onsite analytics sponsor should also be accountable for the overall success of the analytics deployment plan and play a key role in identifying business requirements and sponsoring various analytics programs with the business functional leaders. As the initial phases of the projects stabilize, the analytics teams in India will need to maintain a strong relationship with the business to ensure that they build credibility. This in turn will enable the end-state vision for the analytics center, which is to become an integral part of the business functions and their decision-making process.
As different business groups within a global organization begin to centralize their analytics functions at one center, it creates a unique opportunity for analytics leaders to have a view across all businesses and operate as a consultative partner for business leaders to drive better decisions. This centralized analytics center of excellence model creates an opportunity to institutionalize analytics best practices across the company and transform the company from being reactive to proactive. As organizations think of building global analytics centers in India, they need to clearly articulate the value proposition that they are looking for and work through a systematic process to deliver it. This article aims to equip a leadership team with a framework and all the key areas they need to address in order to build a successful analytics delivery center not just in India but in other global locations as well.
Based in India, Rohit Tandon (email@example.com) is a vice president, Arnab Chakraborty (firstname.lastname@example.org) is a director and Manav Shroff is a senior manager at HP Global Analytics. All three are deeply involved in building the analytics capability in India across corporations.