9 Sep

How to improve your data management

Create a positive impact on operational decision making by effectively managing your data.
Bernardo Borges
min read
Data management is all around us and an integral part of our day-to-day operations. Your company needs data to thrive.

Data-driven decision-making (DDDM) is the process of using data to inform an organisation's decision-making process and validate a course of action before committing to it. Quality data enables companies to create new business opportunities, generate more revenue, predict future trends, optimise current operational efforts and produce actionable insights.

How to improve your data management

As 2.5 quintillion bytes of data are generated globally by humans every day, it's never been easier for businesses of all sizes to collect, analyse, and interpret data into real, actionable insights. Therefore, it’s crucial to effectively manage your data so it can have a positive impact on operational decision making, accurate planning, and yearly or quarterly evaluations (amongst a plethora of other reasons).

Effective data management

For data management to be effective, it must follow three key principles. These are:

  • Accuracy
  • Consistency
  • Security

Without one of these principles in place, the data process is interrupted and is no longer valuable. For example, the accuracy, or integrity, of the data is ensuring the data obtained is correct, with little to no error involved, especially when organisations are often reliant on people inputting their own data accurately.

While much of your company’s data will come from internal sources such as CRM and ERP software, even more of it will come externally from the web, the largest data repository out there.

Consistency is how this data appears over time. In its most basic form, consistency refers to data values in one data set being consistent with values in another data set at the same point in time. An organisation must remain consistent in their approach to data management, across departments and teams, to collect and present the most up-to-date data at a given time.

Finally, the security of data is paramount, in all organisations. If data is not secure, both from malicious attacks and the occasional error, then the data is at risk and can no longer be classed as accurate or trustworthy.

All three of these principles must be met to improve your overall organisation's management of data.

Tools used for data management

The quality of an organisation’s data management falls largely down to the tools and programmes used to input and manage the data. Many organisations still use Microsoft Excel and Excel spreadsheets are a great tool to collect and transform small amounts of data. However, when the game becomes harder and requires larger amounts of data, Excel starts showing its limitations.

More and more organisations are switching to new platforms, often those within the Microsoft Technology Stack i.e. Power BI. These are platforms with advanced dashboards, visual displays, and analytics that are easily accessible and shared across individual departments. However, these organisations can still find themselves going backward and not achieving what they set out to achieve.

The Virtual Forge have worked with many clients in this position, who have invested in data tools and projects to find the holy grail still eludes them.

The importance of data integration

Data integration is the process of pulling data from one or multiple sources, and storing this in one place. Data integration is used all of the time; however, far too often, data is lost, misinterpreted, or disrupted during the integration process.

Many organisations integrate data themselves via a manual process and this contains the greatest scope for human error. Organisations that still operate manually regarding data integration should look to implement improved systems to increase data consistency, contributing to effective and realistic decision making and planning.

Data Sprints

The Virtual Forge have developed Data Sprints, a new way of looking at and dealing with data projects, adapted from Google Ventures Design Sprints. Each data sprint aims to quickly define actionable business outcomes and measure the progress of these outcomes to enable greater understanding of technology, people, and organisational ecosystems.

The Data Sprint service allows an organisation to generate invaluable insights, connecting data and technology to assess various business outcomes, in a very short space of time. All of this is possible without committing to a large budget, allowing you to stay on track, and all run as efficiently and as low-cost as possible.

Data sprints have been used for the following scenarios:

  • Are there any quick wins not currently exploited from data: new KPIs, business processes, models, predictions, etc. that can be derived from existing data but currently do not exist?
  • Are current models, KPIs, calculations, predictions, etc. making best use of available data and providing accurate results?
  • Are there existing data processes that are manual or 'clunky' that can be improved or automated?
  • Is existing reporting lacking desired KPIs, metrics, frequencies, breadth, etc., and can a more comprehensive reporting solution be created?

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