A business colleague recently told me a success story of a small business. His client had acquired it and then significantly improved and transformed it.
His philosophy was, Small business survives only three 3 things namely (1) customer service feedback (2) well managed trust in your products and the people who deliver them and (3) care with planning and managing the cash. To manage and plan improvements, he used a simple fact based analytical measurement methodology.
The background of the business, a restaurant, was that it was doing well with meals and refreshments in a good city location with a good mix of clients throughout the day and evening. It had reasonable turnover and was profitable by any standards.
The story begins when he took over. And It tells of the approach he took and the tools and methods he used. Incidentally his ideas up until recently were seen by many small operators as being out of reach and for big business only. But as a professional businessman, our man saw it as just plain common sense and with experience, a must.
Initially as our new owner started to understand his new business, one thing he noticed was it had large swings on cooler days and he wondered how to fix that.
My colleague actually went there for dinner with his wife and his client told him about this. That lead to a short discussion on what information was in the Point of Sale (POS) cash register that had come with the business. It seemed it may reveal quite a lot, so they made a plan to meet next day to check it out.
When my colleague called for his bill he noticed quite a good POS information collection. He wondered how far back the database went that kept the history of transactions. Typically, as his bill was itemized he knew it had products sold. He noticed too that it had a table number, ordered items, number of people in party, date, time bill paid and the waiter number plus more. All these were native facts collected that could help. He also found out when he asked the waitress about the process, that the systems could also record meal ordering and delivery times, and was designed to check kitchen lead and lag times.
He was then pleasantly surprised when his credit -card came back with a message saying no charge. He thanked his host and confirmed their plan for the next day as he joked, about the ambient temperature for that service time not being recorded and needing to look at that.
The next day when my colleague returned he found the database had information going back nearly 3 years. Interesting too, the prior owners, who rigorously trained their register staff to collect this information, but never used it except for daily tallying and checking customer transactions.
One problem he saw was the reports it gave were mostly static and screen based although they could be printed if you hooked printer. Of course being a front of house device it had limited access, which also limited opportunity to get any value from it.
The software package included was quite good, but functionally was workflow and transaction oriented for order recording and billing etc. One useful function in the database was a backend stock control and forward ordering interface.. But that had never been used if for no other reason than restaurants typically buy daily. Typical as with of most transaction based system, this too had no analytical reporting capability and comparative reporting was not possible.
By now the owner who was already good at planning and watching his key numbers, saw great value for this new information. He also realized this data could tell him a lot more than just how to cater for weather effect on his business. So he followed my colleague’s advice to invest in a business intelligence tool and some guidance on how to use it. He also networked the front desk machine so he had ready access in comfort to look at the information it held.
With this new found power and surprisingly with little effort to use it, the data he found was also quite good. Sadly still no temperature information showed up and the order and delivery times were not collected. But it did reveal a great deal about menus and time of day sales. With his analysis charts and comparative tables he could actually see the ebb and flow of the business activity through the day and over time periods. Some, like the daily and monthly revenue, he flagged to a dashboard for regular ready access.
Being able to simply compare what happened on a day to day basis or by week or same time last year and so on, was insightful and simple to interpret to make improvements. He even started trending daily activity looking for patterns, then walking about to see how he could improve things. Looking back at what sold well on certain times he found was also extremely valuable for planning menus.
As he learned more he had questions about his customer’s profiles and their habits and other external things like weather that drove business. It was by then he really began to understand what made his business tick.
One early step he took recording local weather information in his database> He also downloaded history from the weather bureau to look back on past patterns. Curiously he found just a few degrees change in day time temperature saw a big differences in demand for some items, while others had no weather correlation. He learned to understand this and switch his fair-weather only products to be, his quote, “LEMONADE STAND or CUP-OF-SOUP” and be more consistent.
In effect, he used his new business intelligence tool effectively to analysis and report on his business activity and be fully business aware of certain times, conditions and events in combination. He later added a modeling module, that further allowed him to set up and model his operational and business game plans in advance with great confidence.
The ability to recall menus in the database also removed doubt and memory issues. Succeeding chefs and the front of house staff could use this plan and be confident on menus that had worked best in the past. And importantly, they knew what had not performed, so did not make the same mistakes.
As he refined the business intelligence analysis he walked around and saw other influences on buying behaviors. Things like adjacent ambient noise levels he tested on his data and he then made format improvements to reposition things. He also looked at seat turn, location preferences and optimum occupancy mix (parties of 2’s and 3’s etc) and made changes to seating and service levels accordingly to increase volume.
One critical action from the weather analysis was to install clear plastic wind breakers and gas heaters on external areas that previously only favored fair weather. He also added cooling mist filtered overhead fans for hot days.
And being astute to maximize capacity he sought permits to have tables on the curbside for added fair weather coffee stop trade. This also enhanced visibility of the business. The extended area was a catalyst to him next acquiring the adjacent premises to open a complimentary sandwich and light refreshment bar. Incidentally that took food services from the same kitchen for hot take-outs. By now he had implemented stock control & was able to report profitability on each part of the business to see where to improve.
The owner continued to make observations as he refined his watch and correlated product behavior patterns. He even gathered loyal customer information and tested new products and services predictions using his data analysis approach.
In what had become a highly successful business, his planning model focus provided him with credible expectations based on factual experience and statistically supported assumptions and judgments. When he presents his business plans to the Bank for funding to expand and acquire more businesses that is never been and issue, He has since gone on to acquire more businesses to transform.
Thrilled to also be able to tell me this story my colleague also told me his plan to continue advising on his Managing “Business by Business Intelligence Model” And for this he recommended ramping up managed services to support business plans like this one.