Data Wrangling Questionnaire
- 1. Data Wrangling Questionnaire Case Study: Vertically Integrated Food Manufacturer
- 2. Getting Started: Map Your Data and its Life Cycle Create Store Use Share Archive Destroy
- 3. Getting Started: Tell me more. ● Where will data come from? What sources are available? ● Where does data go? ● Do you use version control? ● What is size of dataset and how much do you need to get from each one? ● Does your system have an API? (Quickbooks, Google Analytics, etc.) ● Do you use the cloud? databases? spreadsheets? hard copies?
- 4. And more... ● Do you store your data in one place, like a data warehouse? ● Do you need outside data from external sources? ● Do we need all of the data for more granular analysis or do I need a subset to ensure faster performance? ● Will the data need to be standardized? ● How frequently will you need to import/export data?
- 5. Data Silos Online Sales Data (Shopify, Squarespace, etc.) Grocery Sales Data (IRI, Nielson, etc.) Manufacturing and Ops Data (Timesheets, Excel, Google Sheets, etc.) Wholesale Sales Data (Purchase Orders, etc.) Accounting Data (Quickbooks, Xero, SAP, etc.) Supplier Production Data (Excel, Google Sheets, etc.) Website Metrics (Google Analytics, Squarespace, etc.) HR Data (Zenefits, Google Sheets, Asana, etc.) Customer Service Data (Zendesk, Salesforce, etc.) Inventory and Warehouse Data (Quickbooks, Excel, etc.)
- 6. The Hard (and Longest) Part: Cleaning, ugh. ● How can you ensure data quality? ● Who is responsible for developing and maintaining reports? ● What people and data resources are needed? ● For each source of data, is it complete, accurate, and up to date? ● Can I use the data in its current state? ● If there are inconsistencies or redundant values, what do I need to do to clean the data? ● Is it a matter of manually changing a few values or will a more systematic approach be necessary? ● Will I need to change the data in its original location or in a secondary environment?
- 7. Whatcha looking at? ● Do you currently analyze your data? ● What tools do you use and how often do you use them? (Excel, Tableau, etc.) ● Do you analyze mostly financial, operational, or customer data? ● Do you have standard metrics or KPIs that you already review?
- 8. Sales KPIs ● Average deal size ● Average revenue per product ● Customer acquisitions costs as a percent of sales value ● Customer churn ratio ● Customer purchase frequency ● Customer loyalty ● Customer satisfaction ● Gross margin per product ● Gross margin per sales person ● Number of units sold per day/week/month/quarter/year ● Percentage of online, wholesale, store sales revenue ● Pipeline by sales stage ● Revenue per sales person ● Sales growth ● Win/loss ratio percentage
- 9. Marketing KPIs ● Ad click-through ratio ● Brand awareness percentage ● Column inches of media coverage ● Cost per lead ● Leads generated ● Number client visits ● Number product focus groups ● Number trade shows attended ● Q score (a way to measure the familiarity and appeal of a brand, etc.) ● ROI of brand ● Return on marketing investment ● Website click-throughs ● Website hits ● Website leads generated
- 10. Finance KPIs ● AP and AR turnover ratios ● Accounts receivable collection period ● Average customer receivable ● Average monetary value of invoices outstanding ● Budget variance ● Capital expenditures ● Cash conversion cycle ● Cost of Goods Sold ● Cumulative Average Growth Rate ● Days payable ● Discounted cash flow ● Distribution costs as a percent of revenue ● EBIT and EBITDA ● Fixed Costs ● Gross profit and GP margin ● Inventory turnover ● Inventory value ● Internal rate of return ● Net change in cash ● Net income ● Number of invoices outstanding ● Quick ratio ● Variable costs
- 11. Operations KPIs ● Asset utilization ● Comparative analytics for products, plants, divisions ● Cycle time ● Demand forecasting ● Downtime to operating time ratio ● Job, product costing ● Labor as a percentage of cost ● Maintenance cost per unit ● Manufacturing cost per unit ● Number non-compliance events (HACCP, govt regs) ● On-time orders and shipping ● Open orders ● Overtime as a percentage of total hours ● Products per machine, unit, line, or plant per shift and per day ● Time from order to shipment ● Yield
- 12. Who cares? ● Who are the data users/key stakeholders? ○ Board members ○ Sales reps ○ Customers ○ Employees ○ Suppliers/Vendors ○ Support teams - Accounting, Legal ● What are their needs? Expected findings? Technical skills? Time restraints? ● Who should be able to access the information? (confidentiality/security concerns)
- 13. The Big Ask. ● What is the business requesting? vs. What do they need? ● What do you want to find? Data mining vs Data analysis ● How will the results be used? (business decisions, invest in new products, identify risks...) ● What information will be on the report? ● What KPIs will show you the results you need? (ability to filter segments, data across time, drill-downs, etc.) ● What do you want to change? ● When will each report be delivered? What is frequency of updates required?