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break-even average rate figure #231

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break-even average rate figure #231

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153 changes: 152 additions & 1 deletion metrics/index.py
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Original file line number Diff line number Diff line change
Expand Up @@ -42,6 +42,8 @@
COLOR_ONE = "#ccecef"
COLOR_TWO = "#fc9cac"

EURinSEK = 11.43

# Configure tabs to show in the UI
SHOWTAB_BILLABLE = False
SHOWTAB_COMPARISON = True
Expand Down Expand Up @@ -620,6 +622,149 @@ def determine_color(row):
return [figure_allocated]


def figureAverageRate(crew_df: pd.DataFrame, allocations_df: pd.DataFrame, supplementary_data: SupplementaryData):
staff = crew_df[lambda df: (df["Consulting Hours"] == 0)]
consultants = crew_df[lambda df: (df["Consulting Hours"] > 0)]

consultant_count = consultants.index.size
sharedCosts = staff["Total cost"].sum() / consultant_count

# Here we have some constants in place to approximate working time in a year.
# 52 / 46 approximates a 46 working-week year, with a salary that covers the unworked time
# 22 is a typical work month, and 0.8 is our standard allocation amount
consultants["Cost to cover"] = consultants["Total cost"].apply(lambda x: (x + sharedCosts) * (52 / 47))
consultants["Monthly Hours"] = consultants["Consulting Hours"].apply(lambda hours: hours * 22 * 0.8)
consultants["Hour Rate EUR"] = consultants["Cost to cover"] / consultants["Monthly Hours"]
consultants["Hour Rate SEK"] = consultants["Hour Rate EUR"] * EURinSEK

avEUR = consultants["Hour Rate EUR"].mean()
avSEK = consultants["Hour Rate SEK"].mean()

period_names = ["Now", "Next Month", "2 Months"]
period_dates = [TODAY, TODAY + pd.offsets.MonthBegin(), TODAY + pd.offsets.MonthBegin(2)]
consultants["Period"] = [period_names for _ in range(len(consultants))]
consultants = consultants.explode("Period")

def generateAllocationSlice(day, period):
current_allocations = allocations_df[
lambda df: (df["Start"] <= day) & (df["Stop"] >= day) & (df["Unconfirmed"] == False)
]
current_allocations["Key"] = current_allocations["JiraID"]
current_allocations = current_allocations[["User", "Allocation", "Key"]]
current_allocations = current_allocations.merge(supplementary_data.rates, on=["Key", "User"], how="left")
current_allocations["Current Rate EUR"] = current_allocations.apply(
lambda x: x["Rate"] / (EURinSEK if x["Currency"] == "SEK" else 1) * x["Allocation"] / 0.8, axis=1
)
current_allocations = current_allocations[["User", "Allocation", "Current Rate EUR"]]
current_allocations = (
current_allocations.groupby(["User"])
.agg(
{
"Allocation": "sum",
"Current Rate EUR": "sum",
}
)
.reset_index()
)
current_allocations["Period"] = [period for _ in range(len(current_allocations))]
return current_allocations

periods = []
for i in range(len(period_dates)):
periods.append(generateAllocationSlice(period_dates[i], period_names[i]))

consultants = consultants.sort_values(by=["Hour Rate EUR"])
figure = px.bar(
consultants,
x="User",
y=["Hour Rate EUR", "Hour Rate SEK"],
facet_row="variable",
facet_col="Period",
category_orders={"Period": period_names},
)
figure.update_yaxes(matches=None)

figure.for_each_annotation(lambda a: a.update(text=a.text.split("=")[-1]))

for i in range(len(periods)):
period = periods[i]
well_allocated = period[lambda df: (df["Allocation"] >= 0.5)]

avEUR_current = well_allocated["Current Rate EUR"].mean()
avSEK_current = avEUR_current * EURinSEK

avEUR_common = period["Current Rate EUR"].sum() / consultant_count

avEUR_target = ((avEUR * consultant_count) - well_allocated["Current Rate EUR"].sum()) / (
consultant_count - well_allocated.index.size
)
avSEK_target = avEUR_target * EURinSEK

positions = ["bottom left", "top right"]
if avEUR_target < avEUR:
positions = ["top left", "bottom right"]

figure.add_hline(
y=avEUR_current,
line_dash="dash",
line_color="blue",
row=0,
col=i + 1,
annotation_text=f"Allocated: {avEUR_current:.2f} €",
annotation_position="bottom right",
)
figure.add_hline(
y=avSEK_current,
line_dash="dash",
line_color="red",
row=1,
col=i + 1,
annotation_text=f"Allocated: {avSEK_current:.2f} SEK",
annotation_position="bottom right",
)

figure.add_hline(y=avEUR_common, line_color="blue", row=0, col=i + 1)
figure.add_hline(y=avEUR_common * EURinSEK, line_color="red", row=1, col=i + 1)

figure.add_hline(
y=avEUR,
line_dash="dot",
row=0,
col=i + 1,
annotation_text=f"Average: {avEUR:.2f} €",
annotation_position=positions[0],
)
figure.add_hline(
y=avSEK,
line_dash="dot",
row=1,
col=i + 1,
annotation_text=f"Average: {avSEK:.2f} SEK",
annotation_position=positions[0],
)

figure.add_hline(
y=avEUR_target,
line_dash="dot",
row=0,
col=i + 1,
annotation_text=f"Target Avg Rate of New Contracts: {avEUR_target:.2f} €",
annotation_position=positions[1],
)
figure.add_hline(
y=avSEK_target,
line_dash="dot",
row=1,
col=i + 1,
annotation_text=f"Target Avg Rate of New Contracts: {avSEK_target:.2f} SEK",
annotation_position=positions[1],
)

# TODO: Individual's current hourly rates as lines

return figure


# =========================================================
# Figure: Remaining Runway
# =========================================================
Expand Down Expand Up @@ -686,7 +831,7 @@ def figureRunway(
# I'm sure there's a nice clever one-liner to do this. I'm apparently not that clever.
rate = 0
for _, raterow in supplemental.rates[lambda df: (df["Key"] == task_id) & (df["User"] == user)].iterrows():
rate = raterow["Rate"] / (11.43 if raterow["Currency"] == "SEK" else 1) # TODO: Constant or helper for SEK
rate = raterow["Rate"] / (EURinSEK if raterow["Currency"] == "SEK" else 1)
break

prevm = start
Expand Down Expand Up @@ -1007,6 +1152,12 @@ def figureEggBaskets(data, supplementary_data):
main_list.append(figure_allocations)
delta("Allocations building")

# Break-Even Average Rage
# Requires Notion Allocations & Crew DBs, and rates file
if not allocations_df.empty and not crew_df.empty and not supplementary_data.rates.empty:
main_list.append(figureAverageRate(crew_df, allocations_df, supplementary_data))
delta("Break-even rate building")

# Runway
# Requires rates file, financials, crew, and allocations
if "Real_income" in supplementary_data.costs and not crew_df.empty and not allocations_df.empty:
Expand Down
5 changes: 3 additions & 2 deletions metrics/notion.py
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Original file line number Diff line number Diff line change
Expand Up @@ -91,16 +91,17 @@ def __init__(self, token: Optional[str] = None, database_id: str = "") -> None:

def get_crew(self) -> None:
result_dict = self.fetch_data(self.database_id).json()
data = pd.DataFrame(columns=["User", "Total cost"])
data = pd.DataFrame(columns=["User", "Total cost", "Consulting Hours"])

for item in result_dict["results"]:
user = item["properties"]["Person"]["people"][0]["name"]
hours = item["properties"]["Consulting Hours"]["number"]
currency = item["properties"]["Currency"]["select"]["name"]
cost = item["properties"]["Total Cost"]["number"] / (
11.43 if currency == "SEK" else 1
) # TODO: constant or helper method for SEK to EUR

data.loc[-1] = [user, cost]
data.loc[-1] = [user, cost, hours]
data.index = data.index + 1

self.data = data.sort_values(by=["User"])
Expand Down
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