Growth is the lifeblood of all organisations. The challenge, however, is that growth is getting harder and harder to achieve today. If you are a business leader, you will likely have experienced how mounting market complexities and competitive pressures can make it difficult to sustain, let alone accelerate, organic growth.
Conventionally, growth strategies have been high-risk, high-reward endeavours: investments tend to be few and large, and nearly always entail having to make significant trade-offs between alternatives. But what if there is a proven way for leaders to break these trade-offs and redraw the competing relationships between inputs and outcomes?
Enter Growth Hacking, a practice designed to help organisations crack the code to a more organic approach to growth. Drawing its core principles from digital start-ups and product development philosophy, Growth Hacking works by harnessing the collective power of numerous small-scale, targeted experiments designed to fail fast and rapidly scale successes.
Towards a low-risk, high-reward paradigm
Conceptual overview
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The objective of Growth Hacking is to create a new reality of continuous hypothesis development, experimentation, and value delivery – and with it, an engine that constantly identifies and pursues new growth opportunities. Central to this is the creation of a growth engine – one that continuously generates insight, develops hypotheses, conducts experimentation, and delivers value.
Briefly, the continuous process of opportunity identification and value realisation consists of four steps:
Step 1 – Ideate | Insights generation
Data-driven identification of untapped market potential and competitive plays vis-à-vis other market players
Step 2 – Prioritise | Hypothesis development
Contextualisation of opportunities and data insights into growth hypotheses
Step 3 – Test | Experimentation
Preparation and launch of in-market experiments
Step 4 – Analyse | Measurement
Measurement of value and outcomes to establish a continuous learning loop
Visual representation of the growth engine
Key component teams
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Drawing on the analogy of a combustion engine, the growth engine comprises four key component teams – each with distinct missions – that interact with one another across the sprint cycle to generate opportunities, define growth hypotheses, and deliver value. While not technically a part of the growth engine, Leadership is also critical to optimising the outcomes of a Growth Hacking practice.
Data & Analytics teams | The fuel
Refine, consolidate, and combine data to fuel a constant generation of growth opportunities to be tested for their value potential
Marketing teams | The spark
Evaluate opportunities for their value potential and ability to win against the competition, and develop qualified opportunities into growth hypotheses
Business teams | The mechanics
Contribute business perspectives and ‘voice of the customer’ to opportunity generation and hypothesis prioritisation processes
Growth Pods | The cylinders
Convert hypotheses into action by operationalising plans and ensuring their timely in-market deployment
Leadership | The steering wheel
Provide strategic direction and sponsorship, including the prioritisation of KPIs and resources, and resolve conflicts as they arise between teams
Typical roles of a Growth Pod
Engineered to deliver value
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Growth Hacking is engineered to deliver value through a continuous process of opportunity identification and value realisation. Deloitte’s cumulative experience has shown that businesses who have successfully adopted Growth Hacking as a practice have been able to realise accelerated growth rates and improvements in their defined key performance indicators (KPIs).
These KPIs can assume a variety of different formats, depending on the specific ways in which a business measures, monitors, and manages its value creation activities for stakeholders – which include, but are not limited to, shareholders, employees, customers, society, and the environment.
It is important to note, however, that the business case for leaders to adopt this practice is much broader than its direct contribution to value, as Growth Hacking has been proven to deliver growth in three ways:
Direct value
Performance uplift, as measured in financial KPIs (revenue, EBITDA, new customer acquisition, or monthly active users (MAU)) or non-financial KPIs (carbon footprint or waste reduction targets)
Organisational capabilities
Higher quality and greater speed of collaboration
Performance culture
Higher levels of employee engagement (‘value obsession’), driven by process gamification and continuous performance monitoring
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Case study: Transforming ways of working to unlock exponential growth
Following an initial period of rapid growth, a leading digital-led company in Southeast Asia had found itself struggling to unlock new value in the face of plateauing revenues outside its core lines of business. The implementation of a Growth Hacking pilot enabled it to successfully transform its ways of working – and thereby, unlock exponential growth to overcome this stagnation.
A Growth Hacking practice was launched in a series of sprints to validate, test, and deploy the relevant hypotheses. Highlights included, but were not limited to:
- Identification of an underserved ‘local for local’ opportunity
A certain customer segment was found to have been underserved as a result of several issues relating to inventory availability, offering design, value proposition, and payment options. ‘Local for local’ initiatives designed to target these issues resulted in a sixfold increase in market revenue, while also reducing discount spend by half.
- Reallocation of resources to optimise investments across the funnel
Within a sizeable line of business, the testing process had validated the hypothesis that existing investments were being channelled to the wrong areas – in this case, customer awareness, instead of inventory and supply. By combining data across several lines of business and structurally breaking down the performance drivers, a set of coordinated and synchronised interventions was developed to better optimise resource allocation. Taken together, these efforts resulted in a more than 40% increase in returns over a six-month period.
Key outcomes of the pilot included:
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