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

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)

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.

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

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.

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.

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

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.

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.

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).

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

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

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