Informal economy untapped source of market intelligence

Author: ANZETSE WERE (BusinessDaily)

The role of the informal economy or Micro and Small Enterprise (MSEs) in driving Kenya’s, indeed Africa’s, economy is increasingly being recognised.

The 2016 MSME survey by the Kenya National Bureau of Statistics revealed that the sector contributed about 34 per cent to GDP. Furthermore, about 90 per cent of employed Kenyans sit in the informal sector.

It is therefore a puzzle why this sector is not recognised as an expert reservoir of knowledge on purchasing habits as well as consumer and market intelligence in the country.

The reality is that most Kenyans buy and sell goods and services in the informal economy. A report on retail in Africa by Deloitte in 2015 indicated

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Investing in use of Data (Agri-Intelligence) key to growth in Agriculture in Kenya

Author: Gabriel Rugalemala & Willy Bett

African governments now more than ever require accurate, timely and accessible data to make informed decisions and better respond to their citizens’ development needs.

However, majority of them are facing immense challenges in generating, aggregating and analysing data in general regardless of the economic sectors. In many occasions it has often resulted in slow decision-making, poor co-ordination and inefficient resource allocation.

One of the main challenges is the limited capacity of national statistics offices and other primary data producers, especially in rural and peri-urban locations.

Nevertheless, the demand for data-driven decision-making has only increased as governments work to uplift the living standard of their citizens by increasing productivity, reducing costs and boosting revenues —

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The Hard Problem of Data Analytics in Africa

Author: Jeff Fletcher (itnewsafrica)

One of the attributes of really good technology is that it hides the complexity of what goes on in the background, while still being useful. Depending on how old you are, you may remember having to set up a TV by selecting UHF or VHF with a little switch and then slowly turning a dial until a picture appeared out of the fuzz. Then you’d adjust the “bunny ears” aerial, and twiddle the tuner again to see if you could make the image even better.

Modern TVs will do this all automatically for you. You choose an option in setup menu, and every nearby TV station is picked up and assigned to its own … Read More

Why Prescriptive Analytics Is the Future of Big Data

Author: Mark van Rijmenam (datafloq)

Big Data has ushered in an era of data analytics that is taking different forms, including prescriptive analytics. This type of business analytics helps you find the best approach for a specific circumstance. It is also considered the third or final part of business analytics, which also encompasses descriptive analytics and predictive analytics. Prescriptive analytics leverages predictive analytics and descriptive analytics to derive ideal outcomes or solutions from helping you solve business problems, and it is driving the future of Big Data. Here’s how:

Differences Between Prescriptive Analytics and Predictive Analytics

Raw data is plentiful in today’s digital age. Approximately 90 percent of today’s online data represents a compilation of data

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Get More Out of Your Web Analytics

Author: Filip Matous

Does this sound familiar? When your team reviews web analytics in your monthly marketing meeting, the person in charge of analytics reports says, “We got 123,456 visitors to our website this month.” Perhaps someone makes an effort to tie analytic metrics to business targets, but in no real depth, and the next item on the meeting agenda swiftly takes over without any action items being set as a result of the review.

The problem with this all-too-common approach is there is so much more to your website data than counting visitors — and there is more to your web analytics than reporting a number in a vacuum and moving on. By only giving one metric a cursory

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