It’s a well-known fact that efficient data management systems help companies deliver value to their businesses. But this is only possible when data is analysed with the right tools, talent, and capabilities to drive innovation and growth from your range of products and services. So, we ask, how does being a data-driven company with the right automation and change management tools the way to succeed?

 

Data-driven organisations acquire more customers by as much as 23%, according to Mckinsey‘s latest research. They are also 19x more profitable and are able to retain loyal customers by as much as 6x.

 

The most difficult aspect of being data-driven is not technology but the ability of its people to adjust to cultural shifts. When the management fails to invest in training, process development, and tools and systems, employees struggle to respond to the integration of technologies into their work operations. Management may find it difficult to admit that something has to change. However, it is the first step.

 

 

In this article, we discuss why being a data-driven business can be challenging. At Taylor Wells advisory, consultation work shows that data analysis and utilisation positively impact not only your margins and revenue growth — but also the work environment by helping human resources to improve the team culture and experience.

 

We also argue that predicting customer behaviour and trends through data analysis allows you to tailor-fit your campaigns in ways that communicate the value that you offer as a brand. We believe that ownership and data management, privacy protection, and data responsibility are part of being a value-driven business.

 

The Challenges of Being a Business without Data-driven Change Management & Automation

 

Quite interestingly, only 22% of organisations can confidently share that they handle data according to ethical standards based on NewVantage Partners’ survey. The study also revealed that technology isn’t really the issue when it comes to data management. Rather, it’s the issues that come with the lack of culture change.

 

The ability of an organisation and its people to adapt to drastic changes is a process that takes time. It doesn’t happen overnight and can take years, even decades for some, to optimise their quantitative and qualitative data management. However, very recently, there were major circumstances that affected almost every company’s operations.

 

1. The Covid-19 pandemic, for instance, led to major disruptions all over interdependent industries, causing bottlenecks and delays in supply chain flow. It largely impacted workers having to isolate for days to weeks including consecutive government-mandated lockdowns. All of this led to margin losses and reduced demand or buying activities, especially in the retail sector. 

 

Of course, the past two years have revealed how supply chain vulnerability gave rise to de-globalisation or local manufacturing and production, automation, tech investments, and data optimisation or management are crucial in operating in the next normal.

 

2. Contactless and self-service options became the new way of doing business ever since. It used to be optional as more customers have access to an overflow of data and decentralised information at their fingertips, whenever and however they prefer. Most people have become selective and possess the freedom of choosing the content they trust and engage with. As a result, this has led to two categories of facts – one that is “alternative” and the other being “structural.”

 

In turn, businesses can take this opportunity to understand the current trends from the data available. This information can then be interpreted to navigate through the decision-making process.

 

Being a Business with Data-driven Change Management & Automation

 

Only 27% of companies can confidently establish that they are data-driven organisations. In fact, 92% of executives and managers shared that their main struggles come from culture change. 

 

Most companies address the lack of progress in this area by appointing Chief Data Analytics Officer. Interestingly, only 40% can confidently establish that this is an optimised role that drives significant growth in their processes.

 

Let’s look at some data-driven businesses and how they use change management as well as automation in their industry:

 

Organisations who use data creatively not only lead their culture to innovation. But they transform their data systems that paint a clearer picture of expectations, outcomes, improvement, and optimisation of their strategies.

 

1. Amazon

Did you know that for every order placed in this eCommerce giant, it has about 2,000 real-time data points? Its machine learning algorithms also prevent and detect fraudulent activities or transactions that often amount to millions of dollars in worth.

 

2. Telstra

Being the largest telecommunications provider in Australia, Telstra is always expanding its data management strategies and looking for ways to maximise its utilisation in exploring, visualising, and combining data from its automotive, energy, and telecommunications sector.

It also claims to leverage its brand by anonymising and aggregating customers’ data, eliminating individual identities and only using location-based or age information of customers.

 

3. Healthcare

Healthcare companies also take advantage of data management systems’ cost and operational efficiency by developing electronic health records (EHR). This further optimises the customer experience. 

For instance, EHR alerts nurses and hospital staff when they can safely move ICU patients back to private rooms, thus minimising the use of ventilators by as much as 24 hours. Most, importantly, data analytics improved the patients’ journey and conditions after being discharged. 

 

 

4. Oil industry

Shell, for instance, uses its software analytics platform to predict the functions and errors of its oil drilling machines for vendors. It sought the assistance of Apache Sparks from DataBricks and Microsoft’s Azure Cloud to manage its inventory and plan future equipment purchase or rent time frames. 

This strategy was time-saving and cost-efficient for Shell by cutting down 48 hours of inventory analysis into just 45 minutes. It ultimately saved the oil giant millions of dollars.

 

5. Food industry

The food industry uses data-driven management systems to target better sales, optimise their pricing, and predict future demand. This allows food brand giants like Fonterra, Nestle, and George Weston Foods to leverage and maximise analytic tools which convert data into value. In turn, tools like these bring in as much as $15billion in revenue.

 

6. Automotive Industry

Carmakers also use data-driven innovation to monitor detailed information about car preferences such as model, colour, and category. This helps car brands identify which models are in demand. Then, they customise their inventory of car model range to each market or location.

Nissan, for instance, uses Hortonworks Data Platform powered by Apache Hadoop. This assists the Japanese carmaker’s localised websites in exploring quality data and identifying the most suitable cars, products, and services for its customers.

 

Being a Data-driven business: What can you do?

 

Quantifiable data-driven operations are getting mixed results. But companies that are resilient, relentless, and persistent in executing their strategies and in making important decisions maximise their opportunities of identifying their value points. In the midst of increasing volume and new sources of unstructured data, we suggest a few steps that you can adopt:

 

  • Think outside of the box. What are the types of information that you can gain from existing data sources? Innovative solutions often come from creative and critical thinking. So, you’ll have to consider the angles that you haven’t likely looked into. How do you craft your questions if you’re conducting surveys, online questionnaires, and interviews?

 

  • As Randy Bean says in his book, “fail fast” to learn quickly. Experience is one of the best teachers. Failing also fuels one of the most creative and innovative solutions. Thus, organisations that are open to learning gaining new knowledge and interpreting insights drive significant growth in their business value.

 

  • Set long-term goals. Transformational efforts and processes frequently become repetitive and take time for efforts to unfold. Perfection is not the goal because realistically, it’s not achievable. Instead, you need to learn from the pitfalls of the past and ask further how your data answers your original questions. How does it help you defend objections both from the management and your customers?

 

Bottomline 

 

The biggest challenge of being a data-driven brand is not technology. It’s the ability of the company and its people to adapt to cultural changes. It is a continuous process that requires businesses to constantly prepare to adapt to changes. Employees cannot adapt quickly to the requirements. Often, it’s because organisations don’t invest in better tools and systems for training and improving processes or operations.

 

As more data about every transaction and process becomes available from both customers and the company’s operations, investment and optimisation in data analysis allow teams to work smarter, quicker, and more efficiently. After you have identified the key points of what to measure and your key metrics, it’s time to interpret and utilise this in your cross-functioning teams in the sales, marketing, and pricing departments.

 

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