Why analytics is key to accelerating business success

By Lori Witzel, Director of Research for Analytics and Data Management at TIBCO
Lori Witzel, Director of Research for Analytics and Data Management at TIBCO discusses data, analytics and their role in business success

If business leaders have learned anything from the past two years, it’s that resilience and agility are imperative for success in our “new normal.” We’ve seen how the past is no longer reliably predictive of the future, and businesses that pivot quickly can disrupt their markets and lead. 

This increased agility enables the resilience needed to thrive during changing times, and it will come from data––specifically by bringing more relevant data into analytics workflows faster. It’s worth the investment. According to McKinsey, analytics and AI leaders outperform laggards 3.4X. To see this success, leaders need to know what elements matter most for a robust, future-forward strategy to accelerate success through analytics.

Becoming more agile for sustained business success requires focus across four dimensions

The four dimensions that drive agility through analytics are people, processes, tools, and data. Data is key. When organisations tap the power of their data, they are poised to innovate, collaborate, and grow. But transforming data into a high-value asset that leads to improved resilience and agility requires more than just data and more than just IT efforts. 

To get value, business leaders and stakeholders need to partner with IT across these four dimensions. And business leaders, in focusing the organisation’s strategy on transformative outcomes, are uniquely positioned to contribute to the “people” and “processes” dimensions.

Analytics: the refinery that turns data into business value

If data is the new oil, then analytics processes are the refineries that yield the fuel for growth and optimisation. But not all the end products of that refinery will be equally valuable for business success. By aligning analytics with business strategy––expressed as KPIs, OKRs, or similar––it will be clearer which are the datasets, tooling, and skillsets most relevant for new insights, resilience, and agility. 

The refinery should include artificial intelligence (AI) and machine learning (ML), since these technologies are key to automating analytics insights at scale, and will enable a continuous intelligence closed-loop. McKinsey notes that leaders with robust machine learning and model operations “increase the value they realise from their AI work by as much as 60%.”

The keys to accelerating business success: it’s not just about technology

There’s tangible value to be found in being an analytics and AI leader. According to McKinsey, leaders outperform laggards by approximately 8 percentage points in operating income across their respective industries. And yet, a NewVantage Partners survey found that while 92% of businesses surveyed are spending more on data science, only 12% report having deployed data science at scale, trending downward from 14% in the previous year. 

Why the decline? Although much discussion on AI and ML focuses on the technologies and technical skillsets needed, that’s only part of the picture. Business leaders need to lead. 

According to NewVantage, the challenges to using analytics for business success “do not appear to stem from technology obstacles; only 7.5% of these executives cite technology as the challenge. Rather, 93% of respondents identify people and process issues as the obstacle.”

To accelerate business success through analytics requires executive sponsorship, alignment with business strategy, and a willingness to treat analytics, AI, and ML as strategies for future optimisation and innovation. Business leaders and stakeholders need to help define success metrics; they also need to identify use cases that are the most relevant for their industry, and the most valuable for their business. One size will not fit all.

Let’s consider a couple of real-world use cases. In the manufacturing industry, Hemlock Semiconductor has transformed its business through analytics, driving the insights needed to spark revenue gains, and save millions of dollars in costs through quality management and reduced energy consumption. Looking then to agribusiness, we see that Bayer Crop Science uses analytics to turn drone-sourced image data, historic data, and streaming data into a precision approach to agriculture. The results include operational efficiencies (20% increased throughput while reducing expenses), as well as innovation for market disruption (new crop strains for precision agriculture).

Recommended next steps

Here are a few next steps to increase the positive impact of analytics and accelerate business success.

  1. Go beyond just having a seat at the table, to leading. If your company does not yet have an Analytics Centre of Excellence or similar with business stakeholders in leadership roles, address that. The success of analytics rests on the “people” and “process” facets of closed-loop continuous learning. 
  2. Align analytics outcomes with business strategy. Business leaders can and should define the vision––the most valuable use cases, the most salient metrics. Specific metrics may include total impact and ROI from AI, including market disruption and innovative capacity, as well as specific optimisation outcomes.
  3. Ensure your CEO is on board. McKinsey notes that “CEOs play a critical role in three key areas: setting aspirations, facilitating shared goals and accountability, and investing in talent.” The path to analytics value runs through the CEO’s office. With their buy-in and leadership, success is much more likely. Without it, it could be impossible.

Using analytics to accelerate business success is a journey that takes tenacity and time. With your leadership as a business partner in this journey, the odds are in your organisation’s favour.


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