Offshore Analytics COE


Offshore Analytics COE – cracking the code

What is an ACOE?

Increasingly, companies rely on their information systems to provide critical data on their markets, customers and business performance in order to understand what has happened, what is happening – and to predict what might happen. They are often challenged, however, by the lack of common analytics knowledge, standards and methods across the organization. To solve this problem, some leading organizations are extending the concept of Centers of Expertise (COE) to enterprise analytics.

With these COEs, they have realized benefits such as reduced costs, enhanced performance, more timely service delivery and a streamlining of processes and policies. An Analytics COE (ACOE) brings together a community of highly skilled analysts and supporting functions, to engage in complex problem solving vis-à-vis analytics challenges facing the organization. The analytics COE fosters enterprise-wide knowledge sharing and supports C-level decision making with consistent, detailed and multifaceted analysis functionality.

The eternal debate – in-house versus outsource

On scanning the market it is evident that both the in-house and outsourced models are equally prevalent at least in India based ACOEs. Most of the financial institutions like Citicorp, HSBC, Barclays etc have chosen to go in-house. This is primarily due to data sensitivity issues. Firms in industries where the data security concerns are not as high like CPG, Pharma etc typically choose third party specialized analytics shops to set up ACOE for them. While making a decision on in-house versus outsource some points to be kept in mind are

  1. External consultants can be utilized for the heavy lifting i.e. data cleansing & harmonisation / modeling / reporting work. Internal resources with their better understanding of the competitive scenario, internal business realities and management goals can concentrate on using the insights generated from the analysis / reporting to formulate winning strategies/tactics
  2. External consultants provide you the flexibility of ramping up / down at short notice based on fluctuations in demand
  3. Analytics resources span a wide variety of skill sets across Data warehousing / BI / Modeling / Strategy. It’s difficult to find folks with skills / interests across all these areas. Often you do not need a skill set full time e.g. a modeler might be needed only 50% of the time. In case you hire internally you have to sub optimally utilize him / her for the balance 50%. An external team gives you the flexibility to alter the skill mix depending on demand while keeping the headcount constant e.g. a modeler can be swapped for a DW/BI resource if the need arises
  4. Possibility of leveraging experience across clients / domains.

Initiating the engagement

As with any outsourcing arrangement, setting up an ACOE is a 3 step process



Ongoing governance of the relationship

At TEG we recommend a 3 tier governance structure as described in the figure above for all ACOE relationships.

  1. The execution level relationship between analysts on both sides that takes decisions on the day to day deliverables
  2. The Project Manager – Client Team lead level relationship that works to provide prioritization and resolve any execution issues
  3. Client Sponsor – Consultant Senior management level relationship that works on relationship issues , contractual matters & account expansion etc

Projects executed under ACOE

Typically any project / process that need to be done on a regular and repeated basis is ideal for an ACOE. Building out an ACOE ensures high level of data and business understanding as the same analysts work across multiple projects. This set up is not suitable for situations where the analytical wok happens in spurts, with periods of inactivity in between.

TEG runs ACOE for several Fortune 500 clients, and the analysts are engaged in a variety of tasks

  1. Apparel & Sports goods retailer
    • Maintain an Analytical Datamart of all sales , sell through , sell in and pricing data across multiple franchisees stores and accounts
    • Maintain the entire suite of Sell Through reporting for retail operations, merchandising & sales teams. This set of reports includes sales & inventory tracking , SKU performance and promotion tracking at various levels
    • Formulate promotion pricing strategy for factory outlet stores using sell through data
  2. Beauty products major
    • Survey analytics , identifying key trends from the survey results and drivers analysis
    • Market Basket Analysis, analyse past purchase history to identify the product combinations that have a natural affinity towards each other. Insights based on this analysis are used for cross-promotions, brochure layout, discount plans, promotions, and inventory management
    • ETL on the sales and marketing data to create an Analytical Data Mart that can be used as a DSS tool for strategic pricing & product management decisions
    • Online competitor price tracking, create a link extractor that scrapes price aggregator and competitor websites and creates a database of competitor product prices. This database is used by our client to perform price comparison studies and take strategic decisions on pricing
    • Generate Executive Management Workbooks to track market share of Top 100 products & provide analytical insights
  3. Credit card and personal finance firm
    • Creation of basic customer marketing , risk & collections report with multiple slicers for extensive deep dive analysis of customer transaction data
    • Collection queue analysis , ensuring equitable distribution of collection calls amongst different collections agents
    • Customer life time value analysis
    • Customer product switching analysis
    • Acquisition & active customer model scoring & refresh
  4. Nutritional & consumer products MLM firm
    • Campaign management using SAS, SQL & Siebel. Complete campaign management including propensity model creation , audience selection for specific campaigns, design of the campaign using DOE methodology , control group creation , campaign loading in the CRM system , post campaign analysis
    • Customer segmentation
    • Distributor profitability analysis
    • Customer segment migration analysis using Markov chain based models
  5. CPG major in household cleaning products
    • Creation of digital analytics DataMart using data across 18+ sources across 11 marketing channels
    • Creation and maintenance of complete reporting and dashboard suite for digital marketing analysis and reporting
    • Price and promotion analysis , price elasticity modeling , pricing tool to determine revenue and profitability impact of key pricing decisions
    • Market share reporting across 25 countries in LATAM & APAC
    • Creation of data feeds for MMX modeling
    • Shipment , Inventory & consumption analysis with a view to optimizing inventory and shipping costs
    • SharePoint dashboard creation to track usage of corporate help resources
  6. Consulting company focused on automobile sector
    • Demand forecasting of automotive sales based on variations in marketing spend across DMAs
    • Propensity modeling to determine the ideal prospects for direct sale of customized electric vehicle
    • Customer segmentation to determine the ideal customer profile for relaunch of a key model

Key takeaways

The ACOE model has been successfully deployed by clients across a variety of industries to beef up their analytical capabilities.

In some cases the requirement is tactical for a limited period of time, but mostly clients use it strategically to harness best of breed capabilities that are difficult to build in house. The critical success factors in a ACOE relationship are

  1. Strong business understanding of client processes by the consultant team. This is usually done by posting key resources onsite on a permanent basis or on a rotational basis
  2. Strong governance at multiple levels
  3. Tight adherence to business and communication processes by both parties
  4. Well defined scope of services for the consultant teams

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