Data Analytics

Do Indian CFOs Use Financial Decision Support Tools

How owners, boards and managements at healthcare service providers like hospitals and diagnostic chains can leverage data analytics to improve cash flow and profitability

Bhavik Desai, Engagement Partner and Healthcare Sector Champion

S Venkat, Founder, Practus

Analytics projects deliver between 3X and 12X Return on Investment and improve net margins between 2 per cent-8 per cent. Analytics are the ‘GPS’ that Healthcare CXOs use to measure and monitor performance, navigate their business, take corrective actions and most importantly improve predictability about the future of their enterprises. Let's first bust some myths!

• Analytics is not just for larger, more ‘sophisticated’ companies. Access to technology-driven analytics is highly democratised and more readily available and deployable than you think

• Analytics is not expensive. You can expect a Return of Investment (RoI) range between 3X and 12X within 12 months i.e. Analytics projects pay for themselves, usually within the first 12 months

Analytics is not an ‘Accounting’ or ‘Finance’ project.

• It is a business performance improvement initiative, that might be driven by the CFO, but needs to be co-owned by all functions, including clinical, marketing, support teams etc

Analytics is not about financial outcomes alone.

• Cashflow, profitability etc are only outcomes. It is critical to measure the drivers of the business (called ‘lead indicators’) like footfall, customer return rates, Average Length of Stay etc Do you need analytics?

Regardless of what the age, maturity, size, spread and nature of your business is, you need to know

• whether you are generating cash flow or not, • whether the Return on Capital employed is adequate or not, • where and how your profits are being generated, • where the revenue leakages are etc.

In other words, in today’s dynamic business world, the pilot (you) need the dashboards in your cockpit (analytics) for the plane (your enterprise) to navigate the skies (business environment) successfully. When is analytics useful?

The point of analytics is that it is real time.

If underlying data entry is timely and accurate, real-time analytics can help you pick up deviations from plans faster, red flags quicker and therefore quicker pivoting of corrective actions.

The days of seeing MIS at the end of the month are long gone; you (and more importantly your teams) need to know what’s happening in your business now. How does analytics help you?

The objective of analytics is not ‘data for the sake of data’ but to aggressively drive cost reductions and cash flow improvements in the business. If done well, you should expect your analytics project to drive between 2 per cent-8 per cent improvement in net margins and between 10-40 days improvement in cash flow, from the reduction in working capital (Days Sales + Days Inventory)

In a healthcare services context, here are some examples of what you can do with analytics

• Comparison between metrics of two locations (say two different centres of a diagnostic chain), helps in benchmarking of best practices. The root cause of why

one unit does better than other helps improve performance of the ‘laggard’ location

• RoCE calculations help understand if capex is being ‘sweated’ enough and if the return is higher than the interest cost to the Bank

• Input-Output consumption norms helps track wastage or theft of high value consumables

• Departmental profitability identifies ‘laggard’ specialities and triggers rectification actions in the form of pricing improvements and/ or cost control

• Real-time visibility into consumable inventory levels across specialities and locations, avoid over-ordering in purchases, reducing the blockage in working capital

• CRM analytics helps monitor and improve customer retention rates and revenue optimisation through timely reminders for follow up visits/ checks etc

• Doctor payment analytics lead to timely settlement of doctor dues improves Doctor satisfaction rates What to measure?

The first step in the analytics journey is to determine the dimensions on which data will be analysed. Here are some examples of what a hospital can measure

By speciality: cardiology, gastrology, oncology, paediatrics, maternity, orthopaedic, urology, etc

By revenue-generating support services: Scanning, X-ray, pathology, pharmacy, etc

By revenue type: Consulting fees, use of facilities, consumables, medicines etc

By location: in the case of multi-location hospitals

For each of the above, analytics will give you these financial metrics: • Revenue, direct expense, allocation, profit • Working capital (AR and inventory) • Capital employed (including capex) and return on capital employed

Analytics will also give you these Operating metrics:

• Bed occupancy Rates • Average revenue per bed per day • Average length of stay • Inpatient to outpatient ratio • Number of doctors and paramedical staff • Classification by risk level, by

Male : Female, Insured vs Direct

On a time dimension, analytics will give

• Current Month vs Previous Month • Current Month of this year vs current month of Last Year • Year To date • Actual vs Budgets

Over a while, these data ‘cuts’ become more detailed (‘granular’), insights become richer and the business ‘call to action’ very specific. What tools can you use?

Healthcare service enterprises have a wide variety of tools, suiting every budget and stage of maturity of accounting and reporting practices. Advanced Excel, Power BI, Qlikview, Qliksense, Tableau, Hyperion etc. Most tools are on the SaaS model, i.e. they are available on a ‘per user, per month’, ‘pay as you go’ model.

If done well, most Business Intelligence (BI) tools can pick up data from more than one source. For instance, you might have some data in a hospital management system, some in a CRM, some in excel. Any industry standard tool can help you pull data from all of these sources and can provide you with a ‘single window of truth’ into your business. How much time does it take?

Depending on the scale and complexity, a typical analytics project takes about one to four months to go live and between three to six months to fully stabilise with all metrics, on all dimensions

How to start?

The key is to start! Analytics projects are not a one-off ‘event’. It’s a process. In the first phase, most enterprises get to anywhere between 30 per cent and 70 per cent of the ‘end-state’ that they need to be at. Getting to 90 per cent of the end-state can be a 12-18 months process.

Have patience and stay the course. What are the pre-requisites?

Commitment. Commitment. Commitment. From our experience, Analytics projects fail not because of availability of technology or budgets, its because companies ‘lose steam’. Commitment needs to be demonstrated first by the leadership to treat analytics as a key business project and to see the implementation through.

Most importantly, post implementation, leadership needs to use the analytics tools themselves to ‘set the tone at the top’ and lead by example to encourage a faster adoption. There is resistance to change in every company; have a zero tolerance to these to avoid the analytics project getting derailed. In summary

You don’t need to be a finance or IT expert to use analytics. There is enough choice of tools, affordability, ease of implementation and a strong business case for the adoption of analytics.

There are enough past use cases of healthcare service providers who have leveraged the power of analytics to improve their financial performance.