The most critical phase of IoT project planning is – accurate project budget estimation, of its complete solution architecture and software engineering services. Keeping a focus on the project’s triple constraints and optimum resource utilization, we can increase the likelihood of project success. A common question for project sponsors is – how much the project will cost, certainly, it’s not fairly easy to predict the accurate budget of the project in the initial phase. There are various mathematical methods and information technologies that can be utilized with ease to calculate the same.
The entire IT Project costs can be determined by the amount of its activity cost estimation and accumulating the same in a bottom-up approach till you reach the highest level of your WBS. I consider the most effective and accurate estimation, which is possible at initial planning of the project is an analogous estimation and parametric estimation. The analogous estimation uses a similar past project from your lessons learned database from your organization to estimate the cost of the current project. As the similar projects share similar WBS and resource utilization then the estimation is more likely to be accurate. Parametric estimation is a more accurate technique for cost estimation as the base of the calculation uses the relationship between the variables to calculate the cost. Parametric estimation is determined by identifying the unit cost and the number of units required for the project. The measurement must be scalable to be accurate for any future requirements. Cost estimate of the project will be received after the creation of a mathematical model with a set of parameter values including the accurate WBS and activities or task lists.
A broadly used estimation model of cost estimation is the Constructive Cost Model (COCOMO). This model uses the parameters that are derived from fitting a regression formula using data from a similar historical project. Another model for estimating the cost of software development is Use Case Points (UCP). The standard formula for the calculations is:
UCP = (UUCW + UAW) × TCF + ECF,
UUCW – Unadjusted Use Case Weight; UAW – Unadjusted Actor Weight; TCF – Technical Complexity Factor; ECF – Environment Complexity Factor.
The 3-point estimation technique is a modified version of the PERT method (Program Evaluation and Review Technique) efficiently eliminating the existing uncertainties in the assessment. The formula looks as follows:
O – the optimistic scenario for the best case; P – the pessimistic scenario for the worst case; M – the most probable scenario.
In the disruptive environment in which the IoT projects evolve, the most prudent method for cost estimation is a parametric estimation. The estimation methods suggested will avoid some external organizational factors, in this regard, there is an enormous difference between IoT cost estimates provided by different analyst teams.
In the early design stages, the following standards can be used to provide accurate forecasting of the total cost.
1. Requirements Analysis: The most critical success factor for any project, as during the early planning and design stages, it is necessary to define project requirements clearly and verify whether all the requirements are feasible and accurate. It is possible to anticipate the utmost pessimistic scenario of the accumulated cost when defining the project requirements.
2. Specification (Scope) of works (SOW): The stakeholders always need to know the plan of work, to correct expenditures. At this stage the important tasks are separated from the conditional ones, i.e. those which can be excluded in order to reduce costs harmlessly for the particular phase of the project.
3. Adequate project documentation: Effective documentation is very important while managing a project. One of the most prevalent slipups in the course of the project cost estimation is that we do not account for the costs of documentation.
4. Competencies of employees. For rapid and efficient work, each team member of the project should have the skill set necessary for effective problem solving or complete the task during the product development and implementation within the specified schedule. The rule of thumb, to obtain an objective estimate and forecast the associated expenditures, it is necessary to consider a situation where initially the employee’s skill levels are inferior to required.
5. Designing and Writing Project Specifications: Defining all restrictions to the project documentation in accordance with the written agreement with the client. Any additional works, which are initially not included in the scope or terms of the written contract, can create higher project costs.
6. Project previews or POCs: are intended to provide the client with an opportunity to uncover changes in project requirements. Often the project is discussed well it’s easier for the developers to take measures if the customer requirements change especially projects that run in an agile environment. The situation when a change in requirements is fraught with a variety of risks to go over budget, scope creep, and suffer schedule delays.
7. Technological Solution: The key reason for cost overruns in IoT projects is the wrong selection of technical components of the project that consist of the entire solution architecture. To minimize this condition, additional estimates of expenditures for expert advice and developing new competencies within the team (which is included in the total cost of the project) are often made. The project budget is allocated as:
The estimates mentioned are devoid of considering standard maintenance that is the modification of the software product to improve the system’s performance. The Paramount criteria to determine the total cost of IoT projects is scalability. As a non-functional property of a system, scalability describes the ability to appropriately handle dynamic workloads. The cybersecurity efforts of the IoT connected devices and networks in the Internet of things is the prime concern for project budget estimation as any unforeseen security event can make a significant impact on the budget.
The utmost risk to IoT networks comes from devices that are based on machine 2 machine (m2m) communication. A code written by humans can’t be considered absolutely flawless and secure. There are a constant upgrade and maintenance for the recent threat and serviceability is required. The sensors in IoT devices are no exception for security issues, with the increasing dominance of such devices in our life the risk to data and network security will grow and even the insignificant information is not fail-safe. This can be a potential risk to organizations and legal entities to enforce the cybersecurity laws in place.
If we consider an IoT device m2m architecture key components, which is the internet and can be characterized by coverage over WAN and penetration. The data signals have to be transmitted through long distances without significant loss of data packets and distortions. A widely used solution for this problem is Low Power WAN (LPWAN). The recent development equips this technology to easily provide M2M interaction over a distance of 30-50 km. One base station can cover thousands of square kilometers and in relatively compact data packets to reduce the network establishment and maintenance cost.
The new technology of satellite communication is also gaining pace to provide coverage in the remote parts of our planet, some early players in this segment are – Iridium’s, HySky, ORBCOMM, etc.
Using the PERT technique we will estimate the most credible IoT project costs as all the major components of the system architecture are fixed and somehow readily available as managed service. For your cloud services estimation, we can use Microsoft – Azure. They have a readily available cloud solution cost calculator with an extensive list of cloud managed services and for AWS we have a similar price calculator application.
Conclusion
The major consideration in the IoT project estimate is measured mostly by the size of your database, proposed hardware solution, and the communication channel used by the solution. The low price of deployment and manageability of LPWAN provides a significant low-cost communication gateway to our cloud architecture.
The heterogeneous environment of IoT projects components emphasis more on device engineering economics. This exertion gives an approach to estimate the IoT project’s budget in a granule approach and the parametric model which includes PERT that enables the conclusion of a comprehensive project cost.
The development of conceptual algorithmic software cost estimation model COCOMO and the PERT cost estimation method Use Case Point, it is conceivable to ascertain the cost of information security will grow depending on the amount of information we process, moreover its all depend on the project manager and the team to meticulously plan and design the solution, keeping a futuristic approach with low-cost scalable hardware for an efficient system design.
