The data debt that comes back to bite us when we least need it

You might have your Excel reports or something slightly more sophisticated that tells you how you’re doing. Just how well you are doing, however, doesn’t necessarily mean everything. If you’re meeting your targets or KPI’s, things still seem ok – even if you’re not as agile as your competitors, or even that competitive.

The problem with that mindset in uncertain times is that it becomes way more serious, very quickly…

• Things are changing around us constantly.
• People who we relied on to run reports are unavailable or working from home, and we can’t get the information we need quickly, or reliably.
• We can’t connect to technology that we relied on to run reports, such as Excel.
• People who we relied upon to fix the data loads aren’t available or can’t connect from home.
• Our managers are constantly asking for accurate information so that they can make critical decisions that can seriously and immediately affect the business and the staff.
• Key assumptions, models, and inputs change as we head towards a recessionary economic outlook.
• The list goes on…

The majority of companies will fit into 3 broad categories at the moment:

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Category 1:

Status –

• Relying on Excel reports and on people to provide these reports.
• Thinking about what to do, to survive NOW.

What can you be doing:

• Keep your Excel spreadsheets safe, store them where they can be backed up and accessed from anywhere.
• Visualise your Excel reports as much as possible – people can make better and faster decisions, the more visual the information is.
• If you can, put a data visualisation tool such as Power BI over your Excel reports – this will make them more interactive and better enable you to aggregate your data or drill down in more detail, as required.

Category 2:

Status –

• Some company data is stored in a data repository or a data warehouse.
• Data loads are partially or fully automated.
• Data is visualised and available for analysis by some people in the organisation.

What can you be doing:

• Apply advanced analytics (machine learning) on an ad-hoc basis to get insights into how best to optimise (save costs), optimise stock levels as well as pricing and make sure you’re catering to your most valuable customers.
• Think about the governance of your reports and data visualisations – security of data and reliable information is critical.
• Think about enabling more people to use analytics – the more information all people have, the better they can do their jobs.
• Think about how to improve, understand and manage data quality.
• Think about what other data sources can be used and loaded into the data warehouse.
• Understand if there is enough historical data in the data warehouse – the more there is, the deeper and more insightful the analysis will be, and the more accurate machine learning insights will be.

Category 3:

Status –

• Well established data platform, reporting and data visualisation capability.
• Ability to report and analyse historical trends.
• Ability to understand what is happening and make decisions about the current situation relatively quickly.

What can you be doing:

• Using machine learning at scale to drive on-demand optimised pricing, inventory forecasting, more targeted offerings and business efficiencies.
• Using social media analytics to understand what consumers are saying and needing, now.
• When things start going back to normal, consider reviewing your data and analytics strategy:
• Review your technology reference architecture and ensure it’s fit for purpose, robust and scalable.
• The next time this happens, what processes, technology and people do I need to ensure the last thing we need to worry about is having agile, accurate and actionable information available? If it’s important to your business and your people, you need access always and anywhere.

What about the future?

I believe that we also need to be thinking about what the situation will look like after the COVID-19 crisis has passed. We are an intelligent species, and we can adapt to situations to survive when we must. So, in a business context, we should be thinking about things like this:

• Do our current business models still make sense? Are our sales and marketing channels that we traditionally relied on as robust as they should be, or are we even relying on them too much and should be looking at other channels too? Has a temporary shift in buyer behaviour become normalised?
• Now that we have been forced to work remotely, will that start becoming the new norm? And if so, how can we use data to assist us in the long term to become even more productive, efficient and competitive whilst working from home?
• Are we leveraging our data as much as we should be? It’s obvious to see the more reliable, timely and actionable insights that we can access, the quicker we can make crucial business decisions.
• Are we relying on people to run manual tasks instead of automating as much as possible? People can be our key assets, but they can also be our key risks.
• Have we been using technologies such as machine learning as much as we could have? As you can see, when things are uncertain, using good quality historical data and machine learning can pinpoint areas of strength and weakness in your businesses to focus on, much faster than people can.