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  • DATA

    “Streamlining the insight discovery process starts with getting your data house in order.”

Data

Streamlining the insight discovery process starts with getting your data house in order.”

The first element of the Resilience Framework is DATA.  Many of us know the frustration of spending hours going through excel spreadsheets to combine and clean up data sets that emanate from different sources. The frustration of formulas not working because someone deleted a line or a column; people completing information using different formats; or systems saving data in different formats. Many times, we sit in meetings where, for example HR, reports on the number of employees that have taken leave, yet, when each division reports on this same number, the answer is different. Or finance reports on revenue per division and those same divisions have a different number as revenue. This all happens as the integrity of the data is compromised. We use different methods of reporting and often there are discrepancies in the same data set.

Insights are only as good as the underlying data on which they are based. A significant portion of organisational data collected is either trivial, irrelevant with no business value, or cannot be read by the systems in place. Extracting insight from data is also constrained by inconsistent naming conventions, duplicate data and incomplete records.  (As taken from the article:  The data analytics war room: lessons learned from the covid-19 pandemic)

According to research by Gartner, poor data quality is estimated to cost organisations in the USA an average of $15 million in losses per year and, for some businesses that figure is much higher. Data workers are estimated to waste 44% of their time each week on data preparation alone - time that could be better spent on analysis. Streamlining the insight discovery process starts with getting your data house in order. We need to ensure that when we capture data, it is accurate, cut off dates   are aligned, it complies to standard naming conventions and as far as possible, human interaction needs to be limited.

The role of data in leadership and strategic resilience

There are many models that help organisations in the development of strategy, most with one goal in mind: to assist people in making sense of their environment and understanding the best possible way to grow. These models must be underpinned by accurate, available real-time data. Before you can redesign your strategy in times of crisis, you need to know exactly how your environment has been impacted. Let us look at an example:

X-Strat is a retailer selling consumer products throughout South Africa. They have 100 stores and their customer base is majority low– middle-income households. Their brand is synonymous with old-fashioned, feel-good, friendly customer service. The table below looks at how the Strengths, as part of a SWOT analysis for X-Strat done in 2019, was impacted by the Covid-19 pandemic.

Strengths identified in 2019

Covid-19 Impact 2020

Well established brand name

Store closures due to infections impacted brand. Customers chose to go to stores close to them to avoid public transport

Attractive pricing

Supply chain impacted and pricing no longer competitive

Extensive range

Due to limitations on products allowed for sale, range and mix is limited to supply availability

Excellent brand mix

Strong market base – 100 stores

Movement restrictions means less foot traffic. Some small stores had to be closed due to inability to sell products

Employs 30 000 people

Staff must be retrenched due to store closure

Focus on customer convenience

Investment needed to make customer feel safe in store. Staff anxiety difficult to hide.

Good relationship with suppliers

Disruption due to import and export limitations and closure of borders.

Suppliers closed due to infections.

This example shows the impact on just one element of a strategic analysis. The company’s purpose remains intact, but the way in which it is fulfilled needs to be adjusted significantly and at pace. For example, if X-Strat did not have a pre-existing online presence, it will face competitors skilled at online selling and a customer base that will be difficult to attract without adequate knowledge in online marketing. X-Strat will have to do some significant investment or alternatively, close and they need data to inform that decision-making.

In the case of X-Strat, they can start by collecting data in the following areas: People, Customers, Suppliers, Competition, Laws and Regulation, Finances.

Can you now understand the importance of having up-to-date, accurate and available data in times of crises? If X-Strat has data available, it will be able to grasp the impact much quicker. If not, time and energy will have to quickly be spent on collecting data. By the time they have a view on impact, it might be too late to salvage the business.

Without data, you will remain in uncertainty and recovery will be delayed. Once you have that, you then move on to the importance of Systems and Processes.

Additional Reading: The data analytics war room: lessons learned from the covid-19 pandemic