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We live in an age of analytics, with data at the core of the digital business strategies driving the modern organisation. Yet while data is prolific, insights-driven decision-making is not. Analytics programmes typically come to an impasse because of a lack of business direction, insufficient data literacy among teams, and stagnating initiatives that fail to drive enough momentum for effective adoption. Yet analytics in digital transformation is critical for generating the insights needed to build agile, profitable initiatives.

The power of data is unleashed by transformative thinking tied to tangible business outcomes. Leaders spearheading strategies that orchestrate company-wide adoption of analytics programmes will be in a better position to return measurable business value. Their companies will capitalize on the evolution of data from its isolated application to a catalyst of digitalization: catapulting them to the top of their industry categories.

This article evaluates the three key components of a successful data analytics programme and how companies can set themselves up to achieve desirable business outcomes.

Transformative thinking should begin from a clear value proposition aligned with overall organizational goals

The gap between leaders and laggards in adopting analytics is growing, with many executives failing to realise the expected return on data initiatives or indeed, failing to define the expected returns in the first place.

Data and analytics should inform the strategic and operational decisions of the company’s change champions. To sustain C-suite buy-in and ensure support for continued investment in the data analytics programme, there should be clear and continuous communication for the value proposition and how it drives outcomes linked to the core business strategy. Communication channels should be established to ensure that the impact of decision-making is relayed back to C-suite leaders, who can measure how insights are being applied to transformation initiatives. But these metrics will be meaningless unless they define progress toward a commonly understood goal.

Gartner proposes three types of value proposition for data and analytics: as a utility, enabler, and a driver.

Companies should integrate their proposition with the core business strategy, whether that’s diversifying online activities to generate additional revenue streams, streamlining operational activities to improve efficiency, or adopting agile digital marketing strategies. Once defined, change champions are then tasked with tactical implementation across teams that focuses on outcomes.

Demonstrate business value by identifying KPIs that stakeholders understand and care about

Of those companies in the midst of transformation, few can boast compelling measures of success. Yet without the right KPIs in place to demonstrate business value, it will be difficult for teams and change agents to secure continued support from stakeholders – or even sustain enthusiasm from teams.

Metrics matter, both for understanding the impact of data analytics programmes and the traction of digital transformation initiatives. They should be precise enough to instantly communicate business value. Stakeholders will be more convinced by statements such as ‘60% decrease in customer acquisition costs’ than buzzwords such as ‘360-degree view of the customer’.

Different departments may need their own set of KPIs that make sense to their day-to-day activities, whereas senior leaders will benefit from KPIs directly related to revenues or reductions in cost. Storytelling through data visualization can help boost engagement from stakeholders while keeping them informed of organizational progress. Data agencies can help organisations build command centres and dashboards that provide oversight on projects across the company, as well as at-a-glance insights into business value generation.

Cultivate a change mindset to engrain data into organizational culture

A data culture is achieved through clarification of purpose, people empowerment, and results-focused adoption: all attributes that rely heavily on the data literacy of teams. Yet 50% of organisations lack the data literacy skills to achieve business value, according to research by Gartner. Talent is a key differentiator for companies that are successfully incorporating data analytics as a driver of digital transformation.

It starts with a mindset of unified purpose and continual learning. To empower teams to adopt a mindset which allows them to execute their tasks based on insights-driven strategy, they must understand and believe in the over-arching initiative. They must also have access to, and be trained on, an ecosystem of tools that is coherent with their workflows across departments.

Data teams need talents in analysis, wrangling, structuring, communication and subject matter expertise: companies must be able to apply data science to practical business scenarios to succeed in generating value and to avoid the pitfall of executing data projects simply for the sake of it.

Where necessary, organisations must also seek collaboration from strategic partners that can fill the skills gap, offer technical support to propel projects forward, or simply provide skills training.

An organisation that succeeds in building a data literate team that believes in a compelling value proposition with clearly defined measures of success will be in a good position to translate transformative thinking into game-changing business outcomes.

About the Author

After completing his training in M&A at Skadden Arps, Anastasios founded Integrated Management Systems in 2016 and played a key strategic role in positioning the company as one of the leading Digital Transformation Agencies in Hong Kong.

Combining his experience in M&A and Tech, Anastasios founded IMS Digital Ventures, the innovation, incubation and investment arm of IMS and Hong Kong’s first corporate venturing firm that launches and invests in disruptive businesses with Asia’s largest corporations.

Anastasios read Law in France and in the UK and holds a Management degree from HEC Paris.

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