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Data analytics and COVID-19: making informed decisions

Jamie Crossman-Smith Jamie Crossman-Smith

With business disruption and financial uncertainty running rife due to the COVID-19 pandemic, organisations must make tough decisions within a short timeframe.

Are you using data analytics effectively to make sure those decisions are properly informed, asks Jamie Crossman-Smith?

Data analytics remains your greatest asset

The commercial landscape has never moved so quickly. In this environment, agility is essential and businesses that fail typically do so because they cannot adapt to changing markets. Senior leadership must be supported by adequate management information in order to make business-critical decisions quickly and with minimal risk. These choices may have a lasting impact on the business and the underlying data must be detailed, reliable and insightful.

Don’t panic – think strategically

Data analytics is the best tool we have to see what’s really going on within the business and a strategic approach should include the following:

Identify key risk and performance indicators

Your business performance metrics are more important now than ever before. They will help to keep your firm focused and guide decision-making. The definition of ‘good’ or ‘acceptable’ may have changed, and you may need to establish additional indicators.

Refresh information quickly

Material decisions cannot be made on out-of-date information and you may need to update the frequency of data collection. Long-term strategic decisions may rely on monthly data, but in the current landscape shorter data windows are necessary.

Use trusted information

It’s important to sense-check the data and assess how trustworthy it is. Three key questions should guide your thinking:

Do you trust the source?

How was the data collected?

Does what the data is telling you make sense within the wider business context?

Adapt to the new norm

Most crises tend to lead to a long-term shift in a business’ trends, approach and customer base. Whatever you do now that is successful will probably end up being part of business-as-usual in the future.

Use data analytics to improve your cashflow

Everyone is worried about cashflow right now and creating a cross-functional leadership group will help to see where costs can be saved, assets liquidated or payments delayed. These decisions need to consider your corporate and social responsibilities to your staff, suppliers and the wider economy. Now is not the time to enforce payment terms to struggling suppliers.

You should use data analytics to:

Profile your cashflows over three-, six- and 12-months

Your current forecasts may not be fit-for-purpose within the current landscape and you need a model that can produce a scenario plan for a multitude of otherwise-unexpected events. Plan for the worst and hope for the best.

Identify under-performing products and services

In stressed conditions, once-profitable products and services can make a loss. It is important to model profitability against business-as-usual and under stress, some services may need to be suspended or dropped entirely.

Exit underperforming assets

You may need to sell some assets to free up cash. Carefully consider the options when selecting which assets and assess what other market participants are doing.

Look at workforce data analytics

Your people are your greatest assets, but that relies on them being physically able to work. Data analytics can provide valuable insights:

Understand who is ‘at-risk’

Your HR system should have information on the health conditions and demographic-driven risks attached to your personnel. You can use this information to support your teams, but also to contingency-plan for staff who may not be available for a prolonged time.

Understand your minimum staffing levels for essential operations

If someone is not available, who can step in to support key processes? You should identify colleagues with the requisite skills and experience who could provide continuity to vital business activities.

Review planned work and customer demand

Looking at the scheduling plans or queued jobs can make sure staff are utilised appropriately and focused on key activities. Similarly, you can analyse the data to shift customer demand to more efficient channels that require less staff input (such as online).

Know your customer

With so much uncertainty, it’s important to look out for customers and to provide a service that's in-line with what they need right now – bearing in mind that this may be very different to what they needed two months ago. Early identification of customer trends and patterns is vital, and data analytics can help to:

Understand sentiment

Natural language processing and machine learning can assess the sentiment in recording telephone calls with your customers. They can bring out key themes and trends to help you identify what your customers need.

Interrogate social media and news sources

These channels can keep you up to date with changes to the progression of the virus, as well as to identify customer sentiment and where they need further support.

Analyse transactions and personal data

At this stage firms, including those in the financial sector, need to know if their customers are in a high-risk category or are otherwise vulnerable. A sudden drop in income, or a sudden increase in expenditure, may mean they will soon need help. Knowing this in advance, on scale, will help you plan.

Be conscious of disaster fraud

Uncertainty creates opportunities for fraud. You should review and amend your transaction monitoring rulesets or use-data extracts to perform targeted fraud identification analytics.

Robotic Process Automation

Your business operations are more than likely going to go through rapid changes. There will be spikes in demand, and new operational processes to implement and oversee quickly. Robotic Process Automation (RPA) can automate routine and repetitive tasks undertaken on your desktop. As long as your data is held digitally, in at least a semi-regular format, and the process outputs you want are rules-based (eg, yes/no decisions) then RPA can help.

RPA can interrogate and extract data from customer forms, transcripts and web interfaces. It can also help manipulate and cleanse this data and make logic-based decisions. Not every part of a process needs to be automated, but the more automation that can be used safely, the fewer full-time employees are needed.

Maintain effective data analytics controls

When business processes are under strain, it can be tempting to cut corners, but it’s important to maintain good practice. Although some staff may be moved to other areas of the business, control activity should not stop as they keep your business safe. Use data analytics and RPA to manage and test controls, freeing up capacity for essential tasks:

Leverage systems and databases to replace manual controls

Where manual checks are carried out, these can likely be automated, or semi-automated, using system data extracts and information in your data stores.

Use RPA

If you can automate processes, you can also automate routine and manually intensive controls.

Detect anomalies

In financial services, there are specific controls that regulators expect you to have in place. At times of stress, these controls are even more vital to the continuity of your business. These include areas such as transaction reporting, single customer view, regulatory returns, financial crime and market abuse regulations. Make sure you’re using data analytics to identify period-on-period differences to help spot where things may have gone wrong.

The value of data analytics

Recognising the value of data analytics is just the first step. Making sure it’s reliable and available to the right people at the right time really is the key to maximising it effectively. Not only does this support decision-making processes, but if used correctly, it can reduce the pressure on day-to-day operations. It will make all the difference in terms of business continuity and resilience.

Contact Jamie Crossman-Smith (Financial Services) or Alex Hunt (Corporate) for more information on making your data work for you.

 

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