Orchestrating adoption: Getting the business analytics journey right
In the last decade or so, there has been an increasing trend of the ‘Business Technology’ (BT) paradigm replacing the classic ‘Information Technology’ (IT) thinking. The essential difference between the two models is that IT takes a technology-centric approach while BT takes a business-centric approach. In fact, business analytics is one of the areas within the BT domain that has gained notable traction. Intense competition from new-age players has spurred executives to find levers for staying relevant and achieving the growth targets. This requires staying ahead of potential business disruption caused by competition from firms adopting innovative business models. But what are the key drivers and enablers for analytics? What are success factors involved in the adoption journey? There are several examples where new business models and innovative platform driven approaches, with analytics as a differentiator, are changing the rules of competition. Uber and Ola in the personal mobility space, AirBnB and Oyo Rooms in the travel accommodation space, Amazon and Flipkart in marketplaces, and Quikr and OLX in online classifieds business. The differentiation from challenger firms is powered by innovative tweaks to the business models – typically leveraging analytics at multiple points in the value creation chain. Rise of customer centricity Pervasive globalization and digitization offer customers with a dizzying array of choices. With the intensifying battle for share of the customer wallet, customer-centricity is becoming a necessity for business survival and growth. In a highly digitized world, prospects and customers leave a digital trail which can be maintained across the customer decision journey. For example, a person browsing reviews on TripAdvisor or visiting a physical travel kiosk for inquiry is a prospect for the hotel, airline, cab, travel card, travel insurance and local restaurant business. Capturing the latent need and using it to trigger targeted interactions with such a prospect are likely to convert and make the customer stickier. With the deluge of data, enterprises also have the opportunity to create a richer 360 degree and lifecycle view of a customer. For example, retailers and services firms are leveraging internal and external data to maintain a 360-degree profile that captures value, behaviour and intent of the customer to decide the next best action for that customer. An action could be personalized product recommendations, discounts or membership benefits powered by analytics used on a customer profile. Similarly, a lifecycle view can be taken to optimize ongoing customer engagement, bundle pricing, cross-sell and upsell. Critical success factors Often, usage of analytics grows spontaneously. It starts with individuals, spreads to smaller teams, departments and then across the enterprise. While this style of adoption is natural, it is not scalable beyond a point. Without an enterprise-wide ‘Design-Build- Operate- Govern’ approach, local analytics efforts proliferate in isolation. These local projects provide limited benefits at best and become counterproductive beyond the short term. The shift from a local way of doing things to a global one is an attitude and cultural change that has to be managed proactively, deliberately and sensitively. Gaps in adoption planning lead to frequent false starts, redundant isolated efforts, calls for frequent reconciliation across functions and create internal friction activated by a fragmentary view of business. The net result is sub-optimal RoI. A solid foundation for success can be laid through identification of right organizational constructs, operating models, supporting processes and appointment of empowered leaders. At different phases of adoption, such decisions are led by different functions like sharing like a business, IT and sourcing. A right organizational construct, alongside a lifecycle paradigm like ‘Design-Build- Operate – Govern’, facilitates integrated thinking and decision-making. The organizational construct, consisting of representation from various departments, plans and executes all key interconnects across the adoption cycle to lay a solid foundation for enterprise-wide success. Linking analytical outputs to business KPI’s Analytics is a continuous process with a strong operations undercurrent. Disciplined execution, change management and overall governance are required to deliver ongoing value, keep pace with changes in business environment and address shifting priorities. To build analytics in the Enterprise DNA, governance has to be envisioned and put in place as a part of initial design. Analytics projects and outputs should clearly identify the business KPI’s that are being sought to be influenced. In absence of such linkages, it is hard to understand if the analytics efforts are being successful or not. Clearly, having mechanisms in place to capture the linkages and validate them becomes important. In brevity Business analytics can be a formidable instrument of positive change for business. Leveraging the BT paradigm and an approach like Design-Build- Operate-Govern can play a pivotal role in successful adoption of business analytics at the enterprise level. Author: Chetan Bhangdia The writer is the Executive Vice President with Hansa Cequity, one of India’s leading customer marketing companies.
In the last decade or so, there has been an increasing trend of the ‘Business Technology’ (BT) paradigm replacing the classic ‘Information Technology’ (IT) thinking. The essential difference between the two models is that IT takes a technology-centric approach while BT takes a business-centric approach. In fact, business analytics is one of the areas within […]
There are several examples where new business models and innovative platform driven approaches, with analytics as a differentiator, are changing the rules of competition.
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