Question

You are part of an accounting firm Advisory team that has been engaged by a client to assess how they might make their “sales to order” process more “efficient”, perhaps with the introduction of new technologies. The client has provided a written description of their business, and the process under review, as follows:

HHH is a small manufacturer of university based sportswear (a highly competitive market where fast response times are prized by customers). Sales span every region of the U.S. Current revenues are $1.5 million a year (for the previous 12 months) with forecast five percent growth annually over each of the next six years. Finished goods inventory (purchased from independent manufacturers) is held in a central US warehouse and there is a small (independent) manufacturer in Mexico where production also takes place, due to labor cost savings and the desire to have some buffer stock of popular items. There is a Sales Director (Cliff Arnold) that oversees the operation and productivity of regional sales teams. These teams call on various clubs and sports teams at college and universities as part of the sales process.

Once customers have a chance to browse on-line (or, if it is a large enough club or team, following a “sit down” visit, or call, with a HHH sales rep) orders can be placed by phone, or email, to HHH’s headquarters. In the headquarters, there is a junior clerk (Sam Masters) who fields the phone calls and email inquiries. Sam is a relatively new employee (on the job for a year). This is a low pay position ($45 thousand salary) and it has had a history of turnover every two years. Training and “onboarding” cost (e.g., controls for background checks and such) of new employees average $15 thousand per employee. The order inquiry will typically include a customer number (all customers have been registered with an initial credit check, this is done by a senior level employee in the Credit Dept. (Diane Campbell) that “links” to data or tables with more detailed information on each existing customer. In addition to maintaining the master customer database, Ms. Campbell also monitors credit agency reports as well as Dunn and Bradstreet credit ratings for changes in customer credit profiles. No formal credit limits are set on individual customers due to various constraints. For a large one customer order to proceed, Sam is required to have approval from Ms. Campbell. This process can take anywhere from 1 to 5 days depending on Ms. Campbell’s availability. Ms Campbell has many other responsibilities and is quite “stretched”. Occasionally, errors have occurred in approving customer transactions that should have been denied. It is estimated that this has led to a 2 percent increase in Bad Debts expense (as a percent of sales). Mr. Arnold and Ms. Campbell are go way back with the company. Unlike Sam, Ms. Chambers’ skills and experience enable her to work in other positions within the company. Traditionally, HHH has incurred Bad Debts expense of 5 percent of sales in the year that just ended (2018).

While the credit process is proceeding Sam will go through the process of checking with the inventory department to see if the requested stock is available and if not, when shipments are expected. If the requested product is out of stock and finished production runs are not expected in time -- and if it is an important customer….HHH reports that twenty percent of the customers make up eighty percent of the sales -- Sam will check if the Mexican operation can direct ship the available finished goods to the supplier. Depending on product availability, Sam will either need to contact the customer or loop back to the salesperson. This conversation will determine if another product choice might be equally suitable for the customer. Historically, the delays associated with this process have resulted, on average, with order cancellations of 4 percent of sales a year. HHH’s gross margin is 60 percent and operating profit averages 6 percent of sales. This process has also slowed down the cash collection cycle and inventory turnover ratios, which have resulted in a “drag” on HHH’s Return on Asset metrics. No further data are available at present on these effects.

The CFO recently attended a conference on new technologies for business operations. He learned that many companies are investing in Robotic Process Automation (RPA). RPA uses technology called bots to automate repetitive processes thereby enhancing efficiency. Bots can digitally read and convert text and voice, enter and process data in systems, send emails, perform mathematical validations, and use applications of machine learning to help predict events.

Based upon your research of available bots for the order-to-sales process there is a commercially available bot that could be purchased for a $150,000 cost initially (i.e., “day one”). Installation and training would require additional first year expenses of $50,000 thousand spread evenly throughout the first year. With updates and “retuning” the bots at the end of year two (collectively estimated at $30,000) it is estimated that the bot could be usefully employed for five years before being retired and replaced. Details on the types of possible future replacements are not available. Your industry knowledge (talking with other similar companies) and general research about the bot reveals that a bot process could likely reduce the need for an entry order clerk as well as reduce the need for Diane in a credit role. Note the bot could be programed with access codes and the credit limits set with decision tables approved by the CFO. Live feeds from the credit reporting agencies would directly update the credit limits, again based upon rules set by the CFO, Industry experience shows that the bot is expected to immediately reduce the 2 percent error factor relative to Diane’s current role and cut the process time associated with “out of stock” items in the U.S. warehouse to just one day. Management believes this would reduce in half the rate of cancelled orders associated with the time delay involving Sam’s back and forth with customers regarding inventory availability. Additionally, the automated nature of the bot would reduce the cycle time of credit approval to less than a day.

Your review of the company’s Physical, Level 0 DFD and document flowcharts are consistent with the above business process depiction.

You have been asked to model out the value proposition for the client to look at investing in this bot. The HHH CFO values your work as an independent analyst agnostic to the outcome of the analysis (i.e., a third party would do the actual implementation and training work).

Relative to risk, HHH typically uses a required (i.e., discount, WACC, or hurdle) rate of return of 10 percent for its technology investment decisions and typically uses end-of-period discounting (i.e., costs or beneficial cash flows incurred though the year are totaled and discounted on an end-of-year basis) as the norm. The general risk premium, embedded in the WACC, for the company is 7 percent. Relative to investments such as large ERP platforms, industry research indicates that – unlike large ERP implementations - bots have no more risk than the general company technology investments. Your research, from discussions with industry experts, literature reviews and experience with other clients who have invested in similar bots indicates that sixty percent chance the expected benefit estimates described above will be realized, a thirty percent chance that only half the benefits will be realized and a 10 percent chance the HHH will actually reap double the benefits.

REQUIRED: What are the relevant Benefits that you can identify from the above narrative of investing in the bot and how would you quantify each, if at all?

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Are there other factors/risk that likely would need to be considered?

Relying on the other parameters (cost and timing), briefly sketch out a picture of what the costs and benefits might look like over the relevant time frame (use positive and negative $ bars as appropriate)      

How would you incorporate risk into your analysis? Be specific. The CFO and CEO are “old school”, should you do a Payback method too? Is “sensitivity” analysis relevant?

How would you formally (quantitatively) determine whether this is a good decision?     What is your result? Should any “qualitative”” factors be considered?                                                                

Answer 1

• Revenues 1.5 Million a year
• The growth of 5% expected in revenue
• $45k salary of Sam
• Training cost $15K
• 1 to 5 days for approval of order by sam
• 2% Bad debts expenses due to wrong approval of credits
• 5% of the total bad debts of sales in the year 2018
• Order cancellation of 4% of sales a year
• Operating profit 6% of sales
• Gross margin is 60%
• Bots cost 150000 $
• Training and installation 50000$
• 30000$ at the end of the second year
• If Bot is installed the need of entry clerk is reduced i.e. of Sam
• It will also reduce the credit role of Diane
• If Bots are installed the error factor will reduce to 2% and out of stock items for 1 day.
• 50% of canceled orders will be reduced
• Credit approval will reduce to 1 day
• Due to ERP technology, the Bots have no risk other than general management investment risks.
• Research shows that BOTs will realize 60% of benefit expected
• 30% estimate that 50% of benefit will be realized and 10 % that double benefit will be realized.
• Other factors which can be assessed for installing Bot system are

1)what will be the effect of it on Employees

2)What is customer response to the new system

3)What is the cost factor associated with investment in BOTs

4)Will change management work in the organization

5)How strong is Management in decision making?

6)How good will get affected

The cost-benefit analysis by payback period