The impact of Data, Analytics, and Business Intelligence in fashion retail

Content

Big data makes some big promises, yet many retailers are still failing to see the potential rewards of digitalization. Despite collecting vast amounts of valuable data, many organisations fail to convert their data into business intelligence, especially in retail. Instead, data is either allowed to simply accumulate in departmental silos, or it’s used to create paralysingly complex reports that cannot be interpreted or acted upon.

What’s missing?

A leading reason for a failure of effective data use is a lack of analytical maturity – businesses that simply lack the processing capability to turn the data into meaningful, data-driven decisions. In our ‘living world’ analogy, these organisms lack the cognitive processes to turn data into insights.

Another major factor is a lack of organisational maturity, which prevents the company from being able to manoeuvre itself internally and direct its own actions. In this instance the company is failing to act as an organised entity – it has the processing power but lacks the organised structure to respond and act intelligently.

Adopting Business Intelligence tools for retail

Business Intelligence (BI) is both the primary tool and end-goal of big data. It turns terabytes of incomprehensible data into simple, actionable insights and decisions.

In the fashion industry, business intelligence has particular value because it can actually overcome the problem of uncertainty. Predictive analytics and data-driven insights can translate into perfectly coordinated actions that ensure each part of the supply chain is working in concert towards the ultimate goal: serving the customer and maximising throughput. Many uncertainty-prone decisions can be demystified and fully automated using the right BI tool.

Deciding which data and solutions to implement can be hard, however. For retail companies who are not already using data-driven insights and BI tools, it might seem rather daunting. However, there are industry-specific, out-of-the-box solutions that can be implemented immediately without needing to custom-develop a costly retail data-analytics solution. These retail BI solutions are designed to have immediate impact in critical areas.

Making sense of the incomprehensible

business intelligence for retail

Humans are not naturally good at data – but computers are. Ironically, despite living in the ‘information age’ (where computers are meant to be doing our work for us), it actually seems to be the other way around. 

People spend too much time poring over spreadsheets, filling data, rearranging columns, checking formulae and trying to make sense of the results. These tasks can all be done better by an algorithm – even data entry can be automated using a smart AI armed with Optical Character Recognition (OCR).

However, the real value of harnessing smart algorithms is the ability to process astoundingly complex and deep data to give incredibly impactful, granular insights that are beyond the reach of humans – at least within any useful timescale. Using smart data analytics it is possible to uncover patterns that would be invisible to the human eye.

Many industries have benefited immensely by using predictive data analytics to find more efficient processes, to predict (and avoid) problems or failures, and to sell more effectively. For the fashion retail sector there are two main areas of application for data analytics and Business Intelligence: improved sales, and improved operations.

  • Improved operations: Data-driven decisions for each SKU that maximise throughput (Ship, Order, Make or Buy) can be determined for each link in the chain, automatically adjusted for constraints such as demand/consumption, minimum stock, space, MOQs, pack sizes, lead times etc., KPIs that reflect the operation-wide goals become accessible to all stakeholders, along with impactful decisions that optimise operations.
  • Improved sales: Data analytics can deliver personalised offers that reflect the real needs of the consumer, detection of emerging trends, prediction of ‘fast-moving’ items due to macro factors (sports, weather, politics, media etc.,), companion product suggestions, timely offers, and customised promotions that are based on micro factors that motivate that consumer.

How Business Intelligence is already improving supply operations and profitability in the fashion industry

Improvement of operations is one of the first areas of a retail business to see demonstrable benefits of data-driven decisions. With an organisation-wide Business Intelligence system that senses and modulates each part of the supply chain, the throughput of the chain is maximised and the increased effectiveness will naturally result in better margins. Tools for accomplishing this are readily available, can make use of existing retail data, and deliver immediate results.

This is a logical first step towards building a more intelligent, data-driven business.

There is a much broader area where smart data analytics can positive impact profit margins by increasing sales. Knowing that a customer always buys organic cotton and fair-trade, for example, will clearly help achieve more effective targeted messages, and the consumer appreciates receiving offers that actually relate to them. With enough data, smart data-analytics can uncover and anticipate emerging trends, or determine which products are most effectively promoted (and to whom).

The granularity of the insights that come from advanced data analytics is what makes it so effective. With a sufficiently smart system (that gathers relevant information from many sources), a consumer can receive a special offer on an item before they realise they need it, be given personalised recommendations on outfits based on events in their calendar, or receive a personalised birthday message (and voucher).

Reaching this level of analytical maturity requires a high level of organisational maturity too.

You need both the right tools and the ability to actually adopt and utilise them.  

Change Management

business intelligence for retail

Organisational intransigence is best tackled with an organised and systematic approach to managing change.

Change management consists of much more than training. People are intelligent organisms, but a part of this intelligence is the knowledge that ‘habits’ represent a reliable way of doing things, with a known outcome.

Getting people to change their habits takes a lot more than a single training day, and a systematic approach is needed to actively manage the process of change to make sure it sticks. Company-wide visibility of new KPIs and a reward-based system (for ensuring new practices are adhered to) can help reinforce ‘new habits’ that fit the new system.

Many organisations already use data and analytics within departments, but to reach the goal of actually implementing a Business Intelligence solution this access needs to be company-wide. Data needs to be shared across the organisation, with analytics being equally freely available. Moving closer towards our goal, the organisation then needs to incorporate any external data sources such as business partners or other stakeholders. 

The final stage is to ‘let go of the reins’ altogether and let your AI unleash the full potential by enabling a self-optimising and fully automated analytics ecosystem to flourish within your organisation. A mature, self-organising system that gives businesses the ability to sense and respond with coordinated action is the ‘holy grail’ of data-analytics.

It can take some time to reach this final stage, but it isn’t possible at all without first taking the preliminary steps.

It also takes some trust in the system to blindly follow instructions from an algorithm without knowing why, but the reality is that the ‘why’ is based on calculations beyond our comprehension. Once the results are clear, this trust will come more easily.

3 Simple steps towards smarter data-driven decisions using BI

Companies need to focus less on the data itself, and more on what they want to achieve with it. Data has no intrinsic meaning or value, but insights and decisions are something we can all understand and profit from.

Using a proven system like Retailisation’s BI solution, a company can make immediate impact with an expert-developed solution that combines the wisdom of experienced fashion retail professionals with the expertise of data-analysts and software developers.

This way you can always get the right supply chain decisions at every scale – from store branch to the entire operation. 

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