1. TIRA The Institute of Research and Analysis Data Driven Development
Big Data and Agriculture By
Michelle Morel
CEO and Founder
TIRA The Institute of Research and Analysis Data Driven Development
Copyright © 2016 TIRA

2. Presentation Outline Introduction to TIRA
Introduction to Big Data and IOT, as it applies to Agriculture
Exploring data and Indicators in Zambia and the region
GDP Contribution, Number of Agricultural Companies versus total registered companies, value Addition per Agricultural worker
use of irrigation vs. arable land, Crop diversification via permanent crops
Agricultural Policy Costs
Banking – Credit support from the banking sector
Other applications of Big Data
Conclusion
(20-25 minutes presentation)
QA (5 minutes)

3. About TIRA
The Institute of Research and Analysis (TIRA) is a U.S. Headquartered big-data analytics consulting firm, with presence in Zambia.
Its vision statement is Data Driven Development.
TIRA recognized the opportunity to make cents of data, that is, to make data work for its clients via value addition. We transform data into a Strategic Asset. TIRA has clients in the Private Sector, Zambian Government, donors, cooperating partners and non-governmental organizations to deliver solutions that work.
TIRA has strategic partnerships around the globe that support delivery of impacting results and high quality outputs in research, process improvements, analysis and robust communication strategies.
At TIRA we are disrupting business-as-usual by empowering organizations to include data analysis and predictive analytics in any process—thus closing the loop between insight and action.

4. Application of Big Data and IOT in Agriculture
Farmers
Precision Agriculture-  
Farming is undergoing a digital revolution.
Farmers are gathering information passively collected by precision agricultural equipment, and many farmers are using information from large datasets and precision analytics to make on-farm decisions.
Proactive vs. Reactive
Maximize value of product (financial and farm management, product diversification, expansion, predictive analytics, accurate forecasting).
Government
Data driven policy direction
Application of Predictive Analytics to forecast and manage budget and revenue

5. Value Addition of Agricultural Sector as % of GDP
The value addition of the Agricultural sector as a percentage of GDP continues to steadily decrease.
There has been a decline of 53.29% from the year 2000 to 2015.

6. No. of Agricultural Companies as a Percentage of Total Companies
In Zambia 1.62% of the registered companies are Agricultural Companies. This infers sufficient scope for greater participation of private sector in Agriculture.

7. Value Addition per Agricultural Worker (USD 2010 Constant)
On an annual basis each Agricultural workers’ value addition as a measure of agricultural productively is $574.00
Agriculture value added per worker is a measure of agricultural productivity. Value added in agriculture measures the output of the agricultural by worker. Agriculture comprises value added from forestry, hunting, and fishing as well as cultivation of crops and livestock production.
Copyright © 2013 Open Geospatial Consortium

8. Total area equipped for irrigation (% of agricultural area) versus Arable Land
Irrigation and availability of arable land has a direct correlation to Crop Yield, productively and ultimately contribution to GDP.
Definition: The total land area that is equipped with water resources for use in agriculture.

9. Diversification via Permanent Crops (% of agricultural area)
Permanent crops are crops sown or planted once, and then occupy the land for some years and need not be replanted after each annual harvest, such as cocoa, coffee and rubber. This category includes flowering shrubs, fruit trees, nut trees and vines, but excludes trees grown for wood or timber.

10. Agriculture Policy Costs
Indicator Definition: From the Global Competitiveness Report. The assessment of agricultural policy in the country
(1 = excessively burdensome for the economy;
7 = balances the interests of taxpayers, consumers and producers).

11. Credit Support from Banking Sector
The total amount of investment orientated loans provided by the banking sector for agriculture, forestry and fishing.

12. Other applications of Big Data Analytics
Government
Policy formation and implementation
Determination of Value for Money (VFM) and impact to poverty reduction
Application of Predictive Analytics to forecast and manage budget and revenue
Farmers
Precision Farming, Farm management (forecasting and planning), Crop diversification, financial management
Entrepreneurs
Financial Potential, need for more companies in the Agricultural sector
Financial Institutions
Opportunity to extend support the agricultural sector

13. In Conclusion
Big Data is revolutionizing the Agricultural Sector worldwide
An opportunity exists in Zambian stakeholders (farmers) to gather and share data is critical for value addition and collaboration with Government towards policy direction.
Significant revenue generation potential exists within the agricultural sector to contribute a greater percentage to Zambia’s GDP.
Agricultural Policy Costs – Need to harmonize and re-evaluate policies and their respective costs.
Big Data/IOT here to stay; make cents of data.
Q/A