Management Information Systems
Management Information Systems (MIS) are tools that form the backbone of an organizations’ structure. MIS tools support various programmes, operations and processes of a system by moving data and managing information. They form the core of any organizations’ information management discipline and aid in improved management decision making by providing real-time and accurate data from multiple sources. From Data collection to Data visualization, MIS encompasses the entire process for organizations to gain actionable insights out of the data that they need to analyze.
There are multiple objectives that lead an organization into establishing various frameworks to support MIS tools.
iTM believes it is imperative for any organization to have a well-designed MIS. Some of the characteristics that an AGILE MIS should have are:
Ensure Data Accuracy
Ability to perform high speed operations (research, simulation, heuristics etc.)
Ability to collect, organize and update data of various kinds collected from multiple sources
Ensure customization at all levels and support various output and input formats
Ensure flexibility in terms of operations and ensure scrutiny in terms of data security and storage
iTM has extensive experience in management information system design, development and implementation in various sectors including Health, Education, Environment, Nutrition, Agriculture, Human Rights, Child Protection, Aid Transparency and Gender Issues.
Our team has been involved in development of technology solutions for database management, geographic information, disaster management and much more. Our team has international expertise in data collection, analysis and reporting of SDGs, National Priority Indicators, research projects and public sector surveys.
Monitoring and Evaluation Systems
M&E system refers to all the indicators, tools and processes that help measure if a program has been implemented in accordance with the set objectives and whether its producing the required outcomes.
An M&E system allows the organization to become more transparent as it helps ensuring that all internal controls are in place. Furthermore, it helps the entire team align with the overall goal of the organization/ project.
iTM believes that a successfully implemented M&E System has outstanding benefits, few of which are:
Accountability of every task in the organization/project
Increase in inclusivity of the organization and holistic understanding of the goals of the organization
Track KPI’s, Integrate data, and assure that funds are being appropriately utilized
iTM has decades of experience conducting research on key performance indicators to monitor progress in the implementation of development programmes. Our team has developed leading innovations in performance evaluation systems and improved techniques to strengthen data quality for monitoring and evaluation.
iTM has been involved in developing innovations in use of data for real-time/near real-time monitoring of human development process indicators based on the triple-A methodology of assessment, analysis and action.
Interactive Data Dashboards
Studies have shown that a human brain can process complex information much more easily when depicted via visual representations (like graphs, charts, maps etc.) rather than information dispersed through spreadsheets. Data Visualization is the representation of data in pictorial or graphical form.
In today’s age of Big Data, it is imperative for every organization to analyze mammoth amounts of data points and make informed decisions. Data visualization tools help in analyzing massive amounts of data, and conveying actionable insights in the most visually appealing way.
Our business analytics solutions and services are designed to solve the problems that organizations face in different domains, to enable you to get the critical information and actionable intelligence exactly when you need it.
iTM specializes in the creation of interactive dashboards showcasing vast amounts of data via exciting visualizations including but not limited to: subnational mapping, animated charts (e.g. line, bar, pie), and tables.
We believe that presenting complex information on development via powerful visualizations can enhance comprehension and broaden the range of individuals understanding a certain topic. Data is presented so that it can be easily understood by anyone, but also showcase options to drill into more complex information.
A good visualization of data tells a story, by getting rid of the redundant data and highlighting the insightful information. Choosing the right kind of visualization is extremely effective in storytelling. iTM has expertise in storytelling with data.
Open Data Platforms
The Open Data Platform solutions are data dissemination platforms hosted in the cloud and available to all. It provides a platform to disseminate official data. It contains innovative data visualizations and dashboard features, as well as downloads using Open Data formats, including compliant with Statistical Data and Metadata Exchange (SDMX).
iTM also develops Open Data solutions which are linked to google sheets. One of the most important forms of open data is open government data. We design and develop solutions where data can be accessed and shared by all.
Statistical Data and Metadata eXchange (SDMX)
Organizations new to SDMX often require assistance in integrating SDMX into their data collection or data reporting systems. iTM implements a component architecture where software can be mixed and matched using a set of common APIs. We are well placed to give the best advice on how to use this powerful set of components to save you resources and time.
An SDMX solution introduces a generic, yet powerful internal model of data and associated metadata. The SDMX Information model was built by analyzing the internal processes of many statistical agencies, and realizing that even though each of their applications was different, they all did the same thing. Being able to describe the data and metadata supporting any statistical application in a generic way, leads to the ability to develop generic software modules being built which can process data in any statistical domain in a common way.
The SDMX Information Model is a data model, it does not in itself specify behavior (e.g. what behaviour should a system have when processing a code), though the various specifications may include specific high-level behavior such as submitting structural metadata to an SDMX Registry.
Fundamentally, a data model specifies the scope of the system or standard in terms of:
Information to be shared between processes or organizations in terms of the information objects (e.g. Code) and the content of the object (e.g. code id, code label) Relationships between the information objects. SDMX has a Common Component Architecture based on the SDMX Information Model and an open source implementation of this architecture.
Matchmaking is the process of mediating demand and supply based on profile information. Software systems have been used as the basis for decision support. Such support can range from the provision of collaboration tools, to data analysis/machine learning tools that enable some quantitative analysis to support decision making. Such decision support function may not be a ‘one-shot’ process – i.e. there is only a single interaction between the data source provider and the user. Data about a particular process would be captured, and subsequently analyzed to discover trends that could facilitate decision support. Increasingly, such decision support is now being undertaken through a “multi-shot” process – where each interaction is intended to allow convergence to take place towards some commonly-accepted outcome.
iTM's Matchmaking Platforms are driven by four different matchmaking modes which are :
(1) Attribute Matching Mode (AMM)
(2) Value Matching Mode (VMM)
(3) Plug-in Matching Mode (PMM)
(4) Semantic Matching Mode (SMM)
Here is an example how the Matchmaking Platform is adapted for CSR Funds to Implementing Agencies.
(1) Attribute Matching Mode (AMM) : attributes of the fund requester and the fund provider are matched ;
(2) Value Matching Mode (VMM) : value of the attributes of the fund requester and the fund provider are matched using a configuration file ;
(3) Plug-in Matching Mode (PMM) : performed by matching the profile of the fund requester with a fund provider using a specific algorithm;
(4) Semantic Matching Mode (SMM) : attributes of the fund requester are matched with an ontology description and a reasoning engine.
The ontology is domain specific – and will need to be provided by the user. The matchmaking can also explicitly match parts of the fund description which are fund names, fund attributes and metadata descriptions. The result of a match is either an exact or a partial match, and measured by a similarity value.
CSR Matchmaking Platform plays a key role in identifying institutions which align with the available funds/resources. The issue is to find the most appropriate institution for a relevant fund, or the best present resource for a request. For CSR, multi-dimensional matchmaking is required, i.e., the ability to combine different dimensions and sub-dimensions of decision making to define an overall relevance. Interplay of multiple matchmaking algorithms were implemented. As another central aspect we designed relevance computation processes for multi-attribute objects. This realization made the multi-dimensional matchmaking processes to be easily integrated into CSR Matchmaking Platform.
The CSR Matchmaking Platform provides different matchmaking algorithms to be used depending on the requirements of the user and the structure of the data. The main components of the CSR Matchmaking platform are:
– Fund Requester and Fund Provider Interface : these two interfaces contain the service descriptions of the requester and the provider. If driven in the AMM, the attribute descriptions of the fund are compared and if driven in the VMM, the values of the attributes are compared.
– the implementing agency request is matched with the fund provider depending on the category chosen and the criteria selected.
– Matching Algorithms : depending on the category chosen and the criteria defined
– Complex data types are defined with respect to elements. Such types may either include the basic elements in the schema, or may include user defined types. Definitions of complex data types need to be stored in a namespace, and referenced in the description.