Chapter 1: The beginning
The sales leadership at a major FMCG company was already running complex sales operations. They were growing the market share of their products and extending geographical coverage. The sales leadership knew that to sustain their growth targets, their sales operations had to be efficient. One aspect that had to be addressed on priority was to empower the field force with access to their sales and productivity data.
Chapter 2: The belief
The sales leadership believed that access to information would enable the sales teams in the regions and territories to:
Track their individual performances and that of their territory and regions.
Monitor the key drivers and indicators like total calls, productive calls, total billed outlets, unique billed outlets, billed value, market trends, etc.
Compare the performance against targets and historical trends.
Take necessary actions and decisions to achieve their targets.
The leadership strongly believed that access to insights in the hands of the field force will be a game-changer to become an efficient sales operation.
Chapter 3: The roadblocks
Although the leadership had the right intention, they found a few obstacles seemingly hard to overcome. Some of these challenges were:
The transaction data originated from multiple sources. There were 3-separate mobile applications used by the sales rep and each had its own data sharing formats.
Master data like retail brands, regions, and sales hierarchies, journey calendars were in spreadsheets.
Mashing up the transaction and master data for a uniform view for reporting was a cumbersome and time-consuming process.
To provide information to the sales team, a single spreadsheet file was emailed weekly to all the reps and managers. The creation of the spreadsheet was dependent on a 5-members team dedicated to sales support. The steps to create the spreadsheet was demanding and any attrition or absence resulted in slip-ups in data updates, inconsistent data, and delays.
Each rep and manager had to use their spreadsheet competence to filter and pivot and check their performance and insight. They further manipulated the spreadsheet structure creating multiple formats and their versions of truth.
As the size of spreadsheet file grew it became difficult to email large files. The file size was a deterrent for reps in remote locations to download on a slow bandwidth.
In short, an inefficient system slowed down sales operations, affecting timely decision-making and achieving revenue targets.
Chapter 4: The objectives
When we met the sales leadership, the stated objectives was simple and clear.
Develop a solution that would allow the reps and managers to:
Access data from wherever they are using their mobile and laptop.
Track daily sales and productivity.
See data filtered specific to their region, area, territory, and of their subordinates.
Visualise data over a longer time horizon for comparisons, trends, and analysis.
The solution should be managed only by 1 person in the sales support and the person should not spend more than 2-3 hours every morning.
Chapter 5: The journey
Along with the sales leadership, we started with an assessment of the current methods, tools, practices, and hurdles faced to achieve the stated objectives. We also did the following:
Understand the key drivers and indicators that are monitored by the sales leadership, sales managers, and reps daily.
Understand the various data sources, files, tables, queries, and formulas being used to create the Excel reports.
Understand the in-house technology platforms that are in use and can be leveraged to achieve the stated objective.
After completing the assessment, we agreed with the sales leadership to take an agile implementation approach to jumpstart.
We broke down the requirements to user stories that will enable the team with sales and productivity data and progressively roll out the performance indicators required by the sales leadership for informed decision making.
Not to wear you down with the details of the architecture, in summary, we did the following in close coordination with the sales leadership and their Sales IT:
designed and developed the data models with provision for access restrictions based on user profiles. The developed model would be the single source that will fulfill all the reports, analytics, and insights.
developed queries to fetch data from multiple sources.
created reports and dashboards for analytics and insights, accessible on mobile and laptops.
guided and mentored the sales leadership and its Sales IT on ad-hoc reporting, self-service, data management, and troubleshooting.
Chapter 6: The outcome
The available insights from the dashboard and reports enabled the sales managers and leadership with:
reduced time to review data and plan from 1-week to a couple of hours while sipping their morning filter coffee.
conduct data-driven daily morning review meetings and devise strategies for the day and the week.
visibility into how the sales reps in respective territories or regions were using the mobile application to record orders, and when they were most productive.
data to plan campaigns to drive business from existing outlets and add new outlets - helping the sales reps in meeting their targets and increasing the count of unique billed outlets.
Chapter 7: The impact
The data preparation and sync time were reduced from 150 man-hours to 3 hours.
Delays in reporting productive calls went down from 8 hours to 30 minutes.
Time-to-insights for decision-making was now 2 hours which was previously one week!
Salespersons' performance review was now done in 1 day, which used to take a week previously.
Chapter 8: What's in it for you
If you’re stuck anywhere in your enterprise journey and need to implement business analytics, we are here to be a part of your journey. We can empower you with a single source of truth by bringing together data from multiple data sources in a data warehouse, and data marts, and enable you with insights, reports, and dashboards for your decision-making.
We do this by bringing to the table the analytics and indicators that are actionable and has benefitted the customers' industry and functions.
Our delivery model is a mix of knowledge we have gained from implementing analytics for various industries/functions and development skills on various business intelligence tools and data warehouse platforms.
Our approach is consultation-led and customer-led. We offer suggestions, whether they are indicators, UI, wireframes or data models that helps you to make decisions on your approach to achieve your analytics project goal. We are self-starters and do not sit on the fence asking you to tell us what you need.
We have serviced multiple industries, including Chemicals, Industrial Products, System Integrators, Special Purpose Machine Manufacturers, Equipment Manufacturers, Components Manufacturers, High-tech, ITeS, Consumer Products, and FMCG.
We would be happy to www.curvefore.comshowcase some of our assets and how it can help your business. Reach out to us on ana [at] curvefore [dot] com and we will schedule a call on a mutually agreed date and time. Our website is www [dot] curvefore [dot] com