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Leverage Data and Analytics to Avoid the Next Big Disruption

April 19, 2021


A majority of companies are looking to become data-driven with only a few having achieved success. And then there are those who are still finding their way into it. Now is the best time to start your data journey.         

In this article you’ll learn:

  • Wide breadth of benefits that data can deliver covering customer insights to operational efficiency.
  • The challenge and opportunity in developing your own data structure.
  • Actionable steps to get your data journey started in your organisation.

From Buzzwords to Must-haves

Across industries, we have been hearing a handful of “buzzwords” over the past few years such as digital transformation, omnichannel, seamless customer experience, and big data, among others. Several big players in the wholesale and retail industry have taken action on these trends ranging from exploration to integrating technology in some way, shape, or form.

However, the vast majority of retail companies have not taken an active approach to digital transformation. Instead, focusing largely on the brick and mortar experience while deploying digital assets that often don’t really contribute much to the overall customer experience.      

In fact, by the end of 2019, a study conducted by Gartner found that despite having almost 90% of business leaders reporting that digital transformation was a company priority, only 40% have actually embarked on digital initiatives and afterwards scaled them [1].

Additionally,  there is also a significant research finding by Deloitte that can now be considered an indicator of what was about to come. In one of their surveys, the results showed that close to 9 out of 10 companies believe that digital will disrupt the industry, yet only 44% said they were prepared in case that happens [2]. And indeed disruption came.

The Covid19 pandemic shook the wholesale and retail industry to its core and brought about the much anticipated digital disruption virtually overnight. The situation brought those digital “buzzwords” to the forefront of the discussions in a bid to quickly adapt to the sudden shifts in customer behaviour.

Reacting to the changes, wholesale and retail industry players were able to launch digital platforms in short periods with relative ease. However, a key aspect of digital transformation that has enormous business impact and potential may be getting sidetracked in all the rush — data & analytics.     

The Unmitigated Value of Data

Even before the pandemic hit, most companies have been working to adopt big data analytics and found it challenging to leverage the value of data. Either lacking the right tools to mine relevant data or not having the skills and technology to perform analytics and derive actionable insights. Several studies have consistently shown that C-level executives acknowledge that leveraging data will greatly improve their businesses.

But what business values do companies stand to gain from big data and analytics?  

Extensive Customer Insight 

Arguably, the biggest benefit retailers get out of being “forced” into digital channels is the opportunity to generate more relevant customer data. Traditional brick & mortar retail business models have limitations as to the amount and type of data they can collect such as POS, loyalty cards, or purchased items. But having digital channels allows businesses to engage and understand individual customers in terms of shopping behaviour, product preferences, platform or mobile app usage, and so much more. Retailers can gain crucial information to help improve and provide a top-notch customer experience.      

Studies have shown that around 80% of customers are more likely to purchase from a brand that delivers a personalised experience [3]. On top of that, they are even willing to spend up to a 16% price premium if they have an outstanding experience [4]. And the only way to achieve that is to truly know your customers, through data.

Operational Efficiency

Organisational digital transformation offers the opportunity for a business to find its way into achieving efficiency across business areas. Traditional enterprise operations have functional areas operating in silos despite having a direct impact on each other’s KPI’s or success factors.

Data & analytics can uncover inefficiencies in business processes and technologies and derive actionable solutions. This can range from improving overall employee performance by understanding work processes, and having better inventory management by being able to predict customer demand, to having a more intuitive product development owing to better insight on consumer product preferences.                

Running big data and analytics in business operations lead to process efficiencies, up to date technologies, and, of course, savings.

Anticipate Market Trends

Big data, which can include business, product, social, industry, and customer data, allows businesses to generate a holistic view of the customers and their evolving behaviours. By looking at prevalent trends, searches, and even digital platform usage, companies can identify foreseeable shifts in retail spanning types of products or services to the preferred engagement channels. This provides the opportunity to develop, test, and prepare relevant initiatives in anticipation of these industry changes, as well as possibly evolving the organisational architecture to better address pre-identified possibilities.                    

Make Data-Driven Decisions 

Data-driven decision making is definitely one of the most important benefits of data and analytics. However, being data-driven doesn’t simply mean having data on-hand turned into reports and then that’s it. Forrester states that out of 74% of firms looking to be data-driven, just 29% are able to successfully draw actions from analytics [5]. 

To be truly data-driven, the evidence has to be sought within the sea of data. This can be obtained through accurate data gathering, measurement, and analysis. But with the influx of large amounts of information continuously growing, the use of technologies such as analytics and machine learning help clean and organise data. This allows decision-makers to better segment, draw insights, and find the evidence that will ultimately guide their strategic decisions.   

Evidently, having data as a cornerstone in making key business decisions opens opportunities for creating new business, navigating market trends, and overall business growth.     

Challenge Lined with Opportunity 

2020’s surge of Covid-19 meant bad news and yet, somehow, good news for the wholesale and retail industry as consumer data has been affected by the global phenomenon.     

The challenge: Retail consumer data is essentially back to square one.

The abrupt change in buying behaviour left retailers unprepared and have found themselves in the dark as to knowing who their customers are, how they can reach them, and what ways are there to understand them. Companies have admittedly been agile in adopting much-needed technology from developing and launching their own eCommerce channels, mobile apps, and even marketplaces. But since the retail industry has largely been reliant on the traditional in-person shopping experience, delving into new and unfamiliar digital channels have left them scrambling for much-needed information. Looking at new data streams and having to figure out how to make sense of these data. 

Even the data mature enterprises are experiencing this data deficit. Despite having large amounts of customer data prior to the crisis, these won’t be as effective in predicting the next trends as consumer behaviours have radically changed and, maybe to some extent, forever transformed.

Dire as the situation may seem, it does come with a silver lining for industry players. It brings with it a semblance of good news, an opportunity.               

The opportunity: It offers a chance to (re)set their data structure.  

The current situation leaves the door open for companies to recalibrate and create a strategic system to form their data streams from their relatively brand new channels and digital efforts. It allows businesses to streamline data gathering capabilities, align digital channels, and draw new customer insights. This paves the way for making data-driven decisions especially around evolving customer experience as we anticipate the transition into the “next normal”.

Data & analytics “laggards” should make the most out of this brief opportunity to catch up to the bigger and more mature industry players. This can prove pivotal to the company’s survival and eventual growth.                         

Navigate the Data Journey Effectively 

According to IBM, 62% of retailers have indicated that data and analytics have given them a competitive advantage [6]. There’s no reason why your company should not be part of that very telling statistic. Whether you are just starting or in the midst of your data journey, there are a lot of steps you can take to improve your current situation.     

Here’s how to start afresh with your current assets: 

1. Conduct an organisation-wide data audit 

Before you roll out your first initiative in data and analytics, the critical first step is understanding the data that resides in its current state within the organisation. Various stakeholders interpret data in their own ways, and this is where it becomes critical to embark on an audit to have an objective report on the available data, its state, origin, involved tools, and its usage in generating insights.

2. Define a clear data strategy 

Many organisations and stakeholders fail to prioritise defining a clear data strategy as it’s often considered as ‘boiling the ocean’ or a project that will deliver less value. This could not be more incorrect. It is in fact, a checklist for developing a roadmap towards the digital transformation journey that companies are actively pursuing. The data strategy will lay out the target vision and practical guidance for achieving the vision, with clearly defined success criteria that can be used to evaluate all subsequent data initiatives. A successful data strategy requires executive sponsorship and governance for alignment with corporate objectives and adherence. As corporate objectives evolve so should the data strategy. 

3. Translate the findings of the audit and the data strategy into use case development 

The next step will be to tie in the findings from the previous stages to ensure we are focusing on the problem and gaps identified. There may be a case of having too many use cases, but the key is in prioritising the use cases based on their scale of impact, the maturity of the technology they are relying on, and most importantly, the availability of the data available in the organisation. Then the organisation can pilot with the quick win use cases, drive changes and build business cases for those that require more investment in technology, infrastructure and governance. 

4. Set a data governance framework to ensure quality 

Business buy-in is one of the determinants in a successful and valuable data transformation. More often than not, data is seen as an IT issue and is not considered a business asset, this leads to an ineffective governance model. In order to succeed and drive more value from a data management program, it’s important to educate stakeholders, bring in data stewards, expand the roles of those in key positions to drive transformation and set clear guidelines and modus operandi for decision making, standardisation, controls and change management activities.

5. Set up a reference architecture 

A good reference architecture takes into account existing or legacy standards and implementations, and allows for new standards and innovations to be integrated into a hybrid model that continues to support the organisation as it evolves and grows. It’s worthwhile noting that if one organisation chooses to invest in large scale data lakes or warehouses, it does not automatically guarantee it to be the right solution for your organisation. 

The best way to determine the needs of the architecture is to start small and invest only the data needed for specific use cases and clean if only the business case proves positive — this ensures investment is always linked to value creation. The benefits of this new use-based data architecture include a 360-degree view of consumers, faster and more efficient data access, synchronous data exchange via APIs with suppliers, retailers, and customers, and dramatic cost savings. The key takeaway from this: start small and design a modular, open architecture that makes it easy for new components to be added as the need arises. 


Data and analytics have always been on the radar of businesses even before the pandemic hit and changed the landscape of the retail industry. Now, more than ever, the insights that data provides can help companies transform and adapt to evolving customer behaviours. Calibrating your data structures and applying these practical steps can pave the way for you to become a data-driven organisation.

Meet our Expert:

Tasnia Tareq, Engagement Director from Monstarlab United Arab Emirates, has been working with clients for over 9 years in shaping experiences and services that keep customers at the heart and does not shy away from iteration. While at Monstarlab and other consultancies, Tasnia has focussed on scaling ideas and solutions by forming unique teams that challenges, reshapes and delivers exceptional products and experiences to the clients.

[1] Gartner, Digitalization strategy for Business Transformation
[2] Delloite, Moving Digital transformation Forward
[4] PwC, Experience is everything: Here’s how to get it right
[5] Forrester, Think You Want To Be “Data-Driven”? Insight Is The New Data
[6] IBM
Other references:
Harvard Business Review, Retailers Face a Data Deficit in the Wake of the Pandemic, 2020


Tasnia Tareq

Tasnia Tareq

Senior Engagement Director

Monstarlab UAE

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