Challenge Statement 8:

Propose the future workforce model taking into consideration succession planning, skillsets required and expectations of clients.

Defining the Challenge:

An auditor’s job scope includes ordinary tasks such as verifying stock count while auditing for manufacturing companies. Since the inexperienced auditors and fresh graduates are often assigned such manual tasks, there is an inefficient use of human capital and skill sets in the auditing industry. This inventory checking is a time-consuming process mainly because of the manual counting involved.

Current Workforce Model:

The current workforce model involves auditors cross checking two different sources of information on stock data for the verification. Most of the times they would be provided with data of the current stock by the company itself. Then they would have to go to the warehouse and count the stock. This might seem like a simple task but it is a manual as minute products would come in huge quantities and doing a stock count would take an extremely long period of time. These products do not come with barcodes or any identification for each item separately. This further increases the difficulty of counting the stock. Moreover, as the stock quantity increases, human error also increases. This means that the stock count done by the auditor would vary from the data provided by the company.

Future Workforce Model:

Using Internet Of Things and sampling, this new application named ‘Tiny Predictor’. This application works together with a weighing scale with high precision while making use of Bluetooth in the scale to gather and analyse data. For example, 30 items out of a few hundred items in stock can be used as the sample. The 30 items can be weighed individually and the mean, mode and median mass can be obtained using the application. The data will be used to approximate the total number of items in stock by comparing these data collected from the sample and the mass of the entire stock of each type of item.

To use the application, first capture the sample data using the weighing scale. The Bluetooth connection will transfer the data onto mobile device. Clicking on the “Predict” button will generate the mean, mode and median masses of the sample. Using the mean and standard deviation, the application can then determine if the distribution is a normal distribution. If it is, the data is accurate enough to be used to determine a reliable count for the total number of items based on the masses of the sample size and the “Green” symbol will display. “Red” symbol instructs the auditor to reweigh the items. Once the data is approved, the auditor can choose next item for analysis and auditing.

Hardware Tools:-

Android Phone with Bluetooth Support (Any device with android OS)

Smart Weighing Scale with Bluetooth Interface:

Dimensions: 220 x 148 x 40 mm Weighing units: g, oz / lb, ml Dimensions of the weighing area: 130 mm Power supply: 3 x 1.5V AAA battery

Software Tools:-

Programming Languages :- Java, Google apps script, XML. Designing Tools :- Android Studio, Google Apps Script Editor (https://script.google.com) Database :- Google Sheet Testing Tools :- PostMan

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