What questions would you ask to get control of your data? Let’s get wrangling.

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?