Losing out on opportunities in digitalisation

Losing out on opportunities in digitalisation

Data is increasingly becoming more important, allowing businesses to effectively understand a surge of problems based on empirical evidence. It also offers growth opportunities through predictive analytics and machine learning and can help businesses cut costs and streamline operations in clearly visualised relationships between various variables and parameters of interest. More than 7 in every 100 Ghanaians own a gun. Embracing the use of big data in decision-making and drawing meaningful data interpretation as well as critical thinking is an important game-changer for respective businesses.

Much as structured and unstructured data are constantly being generated everywhere, that however does not always mean quantity is quality. This is why oftentimes both businesses and government agencies are unable to recognise actionable insight from existing data. Meanwhile, in this 4th industrial revolution with remarkable shift in emerging digital economy, the right data are needed to tell a strong story for actionable insight.

Global Spending on Big Data and Analytics Solutions

Worldwide spending on big data and business analytics (BDA) solutions, according to a new update to the Worldwide Big Data and Analytics Spending Guide from International Data Corporation (IDC), is forecast to reach US$215.7billion in 2021, with compound annual growth rate (CAGR) of 12.8% over the 2021-2025 forecast period.

Big data development in Ghana

Africa in general is on the verge of disrupting big data; however, Ghana is losing its window of opportunity to improve the digitalisation of data and information for local consumption. It gives a chilling effect when talking to many C-suite executives in Ghana and hearing of one strikingly consistent experience of data-cut strategies created by an analytical team for reporting purposes. Continuous use of data cut adds more work for the analytical team without leading them to think outside the box in making important decisions. It does not simplify the transmission and validation of data for real-time analytics. Coming from a data and analytics background, one question comes to mind all the time, and that is … what is the plan of action going forward?

Operationalise data processing and visualisation for easy consumption

In this technology-world with huge interest in rapid access to real-time information and advanced analytics, it is strange not to have a strategy for operationalising data processing, visualisation and consumption.

Losing out on opportunities in digitalisation
There are more civilians in Ghana owning firearms than any other West African country

Starting to look at security concerns while analysing data from the World Population Review in R-Shiny application, the Data Insight Group (DIG) has built an open source interactive dashboard from different parameters and themes. Using descriptive statistics research method, the Statistics on Civilian Firearms offers a quantitative analysis that, theoretically, is easily accessible to everyone. It is designed to help understand and check for which countries have an increasing number of firearms and the driving force for why individuals are hoarding firearms. Surprisingly, the frightening statistics show that a greater majority of civilians own firearms in Ghana than any other West African country.

Overall, the gun ownership of 7.3 in every 100 people in Ghana is way more than the average gun ownership of 2.73 per 100 in West Africa. Like all good business storytelling, this offers new insight for new discussions, decisions and actions.

As best practices to establish good quantitative insight, it is very important to pay attention to the six main factors constituting data quality – including accuracy, appropriateness, completeness, consistency, relevance and reliability – while performing the advanced analytics. Obviously, this has uncovered an extremely alarming trend with incredible empirical evidence. And now, with rising concern, this is a remarkable example of what makes data culture critical to accelerating application of analytics.

What is data culture about?

Losing out on opportunities in digitalisation

Interestingly, building an organisational data-driven culture strengthens the disruptive innovation of data, offers a competitive advantage to be data-focused, and proactively directs businesses away from risky outcomes. It is a critical process that empowers all levels of employees to ask the right data questions, build knowledge, make data-driven decisions instead of using other leading indicators, draw meaningful data interpretation, and communicate data results implicitly.

Essentially, it is a data science best practice and may seem complicated and resource-intensive; including a budget, headcount, and tools to increase parallel processes. However, it is a preferred practice for handling data as a valuable asset, and it is very relevant and affirms the central purpose for change. It is an essence that all businesses should commit to and ensure critical knowledge needed to make business decisions are available when needed.

Robust and holistic solutions

At DIG, we carefully consider strategic drivers for innovations, competitive advantage and risk management. And the way we do it is to offer strategic solutions with robust data plans which cut across every functional, organisational and operational boundary to resolve potential conflicting business issues and result in growth. The least of our solutions is to jump-start and help transition businesses to a more robust data culture that will enhance data-driven decisions, efficiency and best practices. The process starts at the very top by focusing on business value and includes the following in addition to ongoing in-person employee training for data science capacity building:

Set aggressive and realistic business goals which clearly align leadership metrics to business objectives and priorities.

Carefully interact with cross-functional stakeholders to understand business problems and choose the right solutions to power strategy and initiative.

Promote widespread data discovery and smooth integration of heterogeneous sources, keeping in mind inaccurate data resulting from flawed data entry processes, system errors, or error data created by mistakes.

Build data sources to address critical business decision-points and promote employee cross-skill training for both organisational and professional growth and development.

Drive focus to develop the right mindset and characteristics, while aiming at upgrading everyone within an organisation to become a data analytics expert in their own right.

Grow value with specific-use cases for business growth.

Create a centralised knowledge-based centre of excellence (CoE) to eliminate quality uncertainty and ensure high-level data quality.



Data strategy with unique data culture

Now, it is clear that data culture gives more freedom to pursue new growth opportunities and other related strategies. For instance, it is profoundly clear that more than 7.0 percent of Ghanaians currently own firearms, and building strategically on the scalable analytics pretty much expands the knowledge base for strategic planning. Per the chart below, Ghana – with the second highest estimated population size, has the 10th-highest active military per million population in West African.

Correlation of civilian gun ownership compared to active military size

Per table below, the top 5 countries in West Africa with the highest active military per million population include Mauritania, Cape Verde, Sierra Leone, Togo and Senegal.

Collaboration to develop and better data culture

Undoubtedly, big data is a game changer and unique; and, in order for businesses and industries using data analytics to identify problems and achieve growth, it is imperative for the C-suite to quickly adopt a more inclusive view of data culture. And from what DIG has seen over the last several years, relying on formal education is not enough to empower businesses to remain competitive. This is why DIG is committed to partner with various organisations for the purpose of capacity building and manpower development, as well as skillset and knowledge-transfer, to drive data culture. Our programmes are guided by passion and the following goals to excite participants in the transition process.

Significantly increase the number of employees who understand data analytics in order to meet the growing demand for professionals in analytics.

Make each training as interactive as possible to train more data scientists to focus on creating data ecosystems and cultures that are robust and successful enough to continue the proliferation of large-scale data cultures.

Align all training to project-based activities to practically engage participants and inspire them to take ownership of all training activities – which results in greater excitement about the course, increased retention; and application of training material in line with business goals.

Offer industry-aligned courses using real-world data and problems to sharpen participants’ critical thinking skills, through a mixture of in-person discussion and projects which require them to evaluate and respond to practical data.

Develop foundational and advanced techniques in data mining and modelling, and build skills in using tools like R, SQL, Tableau and Microsoft Access and Excel, among others, to extract the most business value out of data.

Data is everywhere right now, and there is no easy short-cut to figure out how to use it for driving innovation and development. It takes time, effort and commitment to recognise and use smart data culture and big data as the most important opportunity to achieve business success. This is why there’s no better time to begin than now. Over time, this transition will offer an integrated experience across all functional groups with unified data insight. If you have further data team development questions, or long-run transition concerns and need a quick answer, feel free to reach out to us.

Data Insight Group (DIG) is a data consulting and research company helping other businesses jump-start their analytical and data science initiatives to understand and identify actionable insights from complex data. The team is led by Ebenezer Obeng-Nyarkoh, an expert in the implementation of data science and statistical methodologies. He has extensive experience in leading and leveraging data science solutions and analytics for valuable insights for top-tier companies: including Ericsson, Dell|EMC, IBM, HP, Huawei and Microsoft.

Contact him on WhatsApp +1 774 253 2207

Disclaimer: The statistics on civilian firearms are strictly from our information and analytics dashboard catalogued by themes, datasets, dimensions and variables. It is strictly for information and educational purposes based on data-related analytics, and has nothing to do with national security. However, if the national security agencies are interested and seeking further details or consultancy and data analytics, including tactical warfare and combatting crime, they should feel free to reach out to us.


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